Bioinformatics - Revision history

Shawndouglas: /* References */ Cats

2022-09-17T19:29:08Z

References: Cats

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	{{Reflist\|colwidth=30em}}		{{Reflist\|colwidth=30em}}

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	[[Category:Informatics]]		[[Category:Informatics]]
			[[Category:Life sciences industry]]

Shawndouglas: Updated URLs for 2022

2022-01-06T17:05:24Z

Updated URLs for 2022

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Shawndouglas: Tweaks for 2020

2020-03-19T22:50:25Z

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Shawndouglas: Added attribution.

2014-04-24T20:41:09Z

Added attribution.

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	* [http://www.embnet.org/ Bioinformatics Without Borders]		* [http://www.embnet.org/ Bioinformatics Without Borders]
	* [http://www.open-bio.org/ Open Bioinformatics Foundation]		* [http://www.open-bio.org/ Open Bioinformatics Foundation]

			==Notes==

			Some elements of this article are reused from [http://en.wikipedia.org/wiki/Bioinformatics the Wikipedia article].

	==References==		==References==

Shawndouglas: Typo

2013-11-05T21:42:39Z

Typo

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	[[File:Computer with microarray.jpg\|thumbnail\|right\|300px\|Female laboratory technician sitting at computer that displays a microarray; DNA microarray technology aids in gene expression analysis and ~~other~~ other bioinformatics functions.]]		[[File:Computer with microarray.jpg\|thumbnail\|right\|300px\|Female laboratory technician sitting at computer that displays a microarray; DNA microarray technology aids in gene expression analysis and other bioinformatics functions.]]

	'''Bioinformatics''' is the application of [[computer science]] and information technology to the field of biology, with a primary goal of understanding biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, and the modeling of evolution.<ref name="BioInfoPolanski">{{cite book \|url=http://books.google.com/books?id=oZbR3GEdmVMC \|title=Bioinformatics \|chapter=Chapter 1: Introduction \|author=Polanski, Andrzej \|publisher=Springer \|year=2007 \|pages=1–9 \|isbn=3540241663}}</ref><ref name="EssBioInfo">{{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|chapter=Chapter 1: Introduction \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=3–9 \|isbn=113945062X}}</ref>		'''Bioinformatics''' is the application of [[computer science]] and information technology to the field of biology, with a primary goal of understanding biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, and the modeling of evolution.<ref name="BioInfoPolanski">{{cite book \|url=http://books.google.com/books?id=oZbR3GEdmVMC \|title=Bioinformatics \|chapter=Chapter 1: Introduction \|author=Polanski, Andrzej \|publisher=Springer \|year=2007 \|pages=1–9 \|isbn=3540241663}}</ref><ref name="EssBioInfo">{{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|chapter=Chapter 1: Introduction \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=3–9 \|isbn=113945062X}}</ref>

Shawndouglas: Added content, updated refs.

2013-11-05T21:42:05Z

Added content, updated refs.

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	[[~~Image~~:~~Genome viewer screenshot small~~.~~png~~\|thumbnail\|right\|~~220px~~\|~~'''Map of the human X chromosome''' (from the NCBI website). Assembly of the human genome is one of the greatest achievements of~~ bioinformatics.]]		[[File:Computer with microarray.jpg\|thumbnail\|right\|300px\|Female laboratory technician sitting at computer that displays a microarray; DNA microarray technology aids in gene expression analysis and other other bioinformatics functions.]]

	'''Bioinformatics''' is the application of [[computer science]] and information technology to the field of biology, with a primary goal of understanding biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, and the modeling of evolution.<ref name="BioInfoPolanski">{{cite book \|url=http://books.google.com/books?id=oZbR3GEdmVMC \|title=Bioinformatics \|chapter=Chapter 1: Introduction \|author=Polanski, Andrzej \|publisher=Springer \|year=2007 \|pages=1–9 \|isbn=3540241663}}</ref><ref name="EssBioInfo">{{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|chapter=Chapter 1: Introduction \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=3–9 \|isbn=113945062X}}</ref>		'''Bioinformatics''' is the application of [[computer science]] and information technology to the field of biology, with a primary goal of understanding biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, and the modeling of evolution.<ref name="BioInfoPolanski">{{cite book \|url=http://books.google.com/books?id=oZbR3GEdmVMC \|title=Bioinformatics \|chapter=Chapter 1: Introduction \|author=Polanski, Andrzej \|publisher=Springer \|year=2007 \|pages=1–9 \|isbn=3540241663}}</ref><ref name="EssBioInfo">{{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|chapter=Chapter 1: Introduction \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=3–9 \|isbn=113945062X}}</ref>
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	The area of research within computer science that uses genetic algorithms is sometimes confused with computational evolutionary biology, but the two areas are not necessarily related.		The area of research within computer science that uses genetic algorithms is sometimes confused with computational evolutionary biology, but the two areas are not necessarily related.

	~~===High-throughput image analysis===~~
	Computational technologies are used to accelerate or fully automate the processing, quantification, and analysis of large amounts of high-information-content biomedical imagery. Modern image analysis systems augment an observer's ability to make measurements from a large or complex set of images by improving accuracy, objectivity, or speed. A fully developed analysis system may completely replace the observer. Although these systems are not unique to biomedical imagery, biomedical imaging is becoming more important for both diagnostics and research. Some examples are:

	* high-throughput and high-fidelity quantification and sub-cellular localization (high-content screening, cytohistopathology, [[Bioimage informatics]])
	* morphometrics
	* clinical image analysis and visualization
	* determining the real-time air-flow patterns in breathing lungs of living animals
	* quantifying occlusion size in real-time imagery from the development of and recovery during arterial injury
	* making behavioral observations from extended video recordings of laboratory animals
	* infrared measurements for metabolic activity determination
	* inferring clone overlaps in DNA mapping, e.g. the Sulston score

	===Literature analysis===		===Literature analysis===

	The sheer amount of published literature makes it virtually impossible to read every paper, resulting in disjointed subfields of research. Literature analysis aims to employ computational and statistical linguistics to mine this growing library of text resources. For example:		The sheer amount of published literature makes it virtually impossible to read every paper, resulting in disjointed subfields of research. Literature analysis aims to employ computational and statistical linguistics to mine this growing library of text resources. For example:
	* abbreviation recognition - identify the long-form and abbreviation of biological terms,
			* abbreviation recognition - identify the long-form and abbreviation of biological terms
	* named entity recognition - recognizing biological terms such as gene names		* named entity recognition - recognizing biological terms such as gene names
	* protein-protein interaction - identify which proteins interact with which proteins from text		* protein-protein interaction - identify which proteins interact with which proteins from text
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	===Prediction of protein structure===		===Prediction of protein structure===
			[[File:Gene-homology.svg\|thumb\|260px\|The idealized evolution of a gene lines is shown from a common ancestor in an ancestral population, descending to three populations labeled A, B, and C. There are two speciation events, each occurring at the junctions shown as an upside down Y. There are also two gene-duplication events, depicted by a horizontal bar.]]
			Protein structure prediction is another important application of bioinformatics. The amino acid sequence of a protein, the so-called primary structure, can be easily determined from the sequence on the gene that codes for it. In the vast majority of cases, this primary structure uniquely determines a structure in its native environment. (Of course, there are exceptions, such as the bovine spongiform encephalopathy (a.k.a. Mad Cow Disease) prion.) Knowledge of this structure is vital in understanding the function of the protein. For lack of better terms, structural information is usually classified as one of ''secondary'', ''tertiary'', and ''quaternary'' structure. A viable general solution to such predictions remains an open problem. As of now, most efforts have been directed towards heuristics that work most of the time.<ref name="FoundCompGeno" />

	Protein structure prediction is another important application of bioinformatics. The amino acid sequence of a protein, the so-called primary structure, can be easily determined from the sequence on the gene that codes for it. In the vast majority of cases, this primary structure uniquely determines a structure in its native environment. (Of course, there are exceptions, such as the bovine spongiform encephalopathy – a.k.a. Mad Cow Disease – prion.) Knowledge of this structure is vital in understanding the function of the protein. For lack of better terms, structural information is usually classified as one of ''secondary'', ''tertiary'' and ''quaternary'' structure. A viable general solution to such predictions remains an open problem. As of now, most efforts have been directed towards heuristics that work most of the time.		One of the key ideas in bioinformatics is the notion of homology. In the genomic branch of bioinformatics, homology is used to predict the function of a gene: if the sequence of gene ''A'', whose function is known, is homologous to the sequence of gene ''B,'' whose function is unknown, one could infer that B may share A's function. In the structural branch of bioinformatics, homology is used to determine which parts of a protein are important in structure formation and interaction with other proteins. In a technique called homology modeling, this information is used to predict the structure of a protein once the structure of a homologous protein is known. This currently remains the only way to predict protein structures reliably.<ref name="FoundCompGeno" />

	One of the key ideas in bioinformatics is the notion of homology. In the genomic branch of bioinformatics, homology is used to predict the function of a gene: if the sequence of gene ''A'', whose function is known, is homologous to the sequence of gene ''B,'' whose function is unknown, one could infer that B may share A's function. In the structural branch of bioinformatics, homology is used to determine which parts of a protein are important in structure formation and interaction with other proteins. In a technique called homology modeling, this information is used to predict the structure of a protein once the structure of a homologous protein is known. This currently remains the only way to predict protein structures reliably.

	One example of this is the similar protein homology between hemoglobin in humans and the hemoglobin in legumes (leghemoglobin). Both serve the same purpose of transporting oxygen in the organism. Though both of these proteins have completely different amino acid sequences, their protein structures are virtually identical, which reflects their near identical purposes.		One example of this is the similar protein homology between hemoglobin in humans and the hemoglobin in legumes (leghemoglobin). Both serve the same purpose of transporting oxygen in the organism. Though both of these proteins have completely different amino acid sequences, their protein structures are virtually identical, which reflects their near identical purposes.

	~~Other techniques for predicting protein structure include protein threading and ''de novo'' (from scratch) physics-based modeling.~~		===Molecular Interaction===

	~~===Molecular Interaction===~~		Efficient software is available today for studying interactions among proteins, ligands, and peptides. Types of interactions most often encountered in the field include protein–ligand (including drug), protein–protein and protein–peptide.
	Efficient software is available today for studying interactions among proteins, ligands and peptides. Types of interactions most often encountered in the field include ~~– Protein–ligand~~ (including drug), protein–protein and protein–peptide.

	Molecular dynamic simulation of movement of atoms about rotatable bonds is the fundamental principle behind computational algorithms, termed '''docking algorithms''' for studying molecular interactions.		Molecular dynamic simulation of movement of atoms about rotatable bonds is the fundamental principle behind computational algorithms, termed '''docking algorithms''' for studying molecular interactions.

	====Docking algorithms====		====Docking algorithms====
	In the last two decades, tens of thousands of protein three-dimensional structures have been determined by X-ray crystallography and ~~Protein~~ nuclear magnetic resonance spectroscopy (protein NMR). One central question for the biological scientist is whether it is practical to predict possible protein–protein interactions only based on these 3D shapes, without doing protein–protein interaction experiments. A variety of methods have been developed to tackle the ~~Protein–protein~~ docking problem, though it seems that there is still much work to be done in this field.
			In the last two decades, tens of thousands of protein three-dimensional structures have been determined by X-ray crystallography and protein [[nuclear magnetic resonance spectroscopy]] (protein NMR). One central question for the biological scientist is whether it is practical to predict possible protein–protein interactions only based on these 3D shapes, without doing protein–protein interaction experiments.<ref name="FoundCompGeno" /> A variety of methods have been developed to tackle the protein–protein docking problem, though it seems that there is still much work to be done in this field.

	==Software and tools==		==Software and tools==
	[[Software]] tools for bioinformatics range from simple command-line tools, to more complex graphical programs and standalone web-services available from various ~~[[List of~~ bioinformatics companies~~\|bioinformatics companies]]~~ or public institutions.
			Software tools for bioinformatics range from simple command-line tools to more complex graphical programs and standalone web-services available from various bioinformatics companies or public institutions.

	===Open source bioinformatics software===		===Open source bioinformatics software===
	Many free and open source software tools have existed and continued to grow since the 1980s.<ref name=obf-main>{{cite web\|title=Open Bioinformatics Foundation: About us\|url=http://www.open-bio.org/wiki/Main_Page\|work=Official website\|publisher=Open Bioinformatics Foundation\|accessdate=10 May 2011}}</ref> The combination of a continued need for new algorithms for the analysis of emerging types of biological readouts, the potential for innovative ''in silico'' experiments, and freely available open code bases have helped to create opportunities for all research groups to contribute to both bioinformatics and the range of open source software available, regardless of their funding arrangements. The open source tools often act as incubators of ideas, or community-supported plug-ins in commercial applications. They may also provide ''de facto'' standards and shared object models for assisting with the challenge of bioinformation integration.

	The range of open source software ~~packages includes titles such as Bioconductor~~, ~~BioPerl, BioJava, Bioclipse, EMBOSS, Taverna workbench, and UGENE~~. In order to maintain this tradition and create further opportunities, the non-profit Open Bioinformatics Foundation ~~<ref name=obf-main />~~ have supported the annual Bioinformatics Open Source Conference (BOSC) since 2000.<ref name=~~obf~~-bosc>{{cite web~~\|title=Open Bioinformatics Foundation: BOSC~~\|url=http://www.open-bio.org/wiki/BOSC\|~~work~~=~~Official website~~\|publisher=Open Bioinformatics Foundation\|accessdate=~~10 May 2011~~}}</ref>		Many free and [[:Category:Bioinformatics software (open source)\|open-source bioinformatics software]] tools have existed since the 1980s.<ref name="OBF-Main">{{cite web \|url=http://www.open-bio.org/wiki/Projects \|title=Open Bioinformatics Foundation: Projects \|publisher=Open Bioinformatics Foundation \|accessdate=05 November 2013}}</ref> The combination of a continued need for new algorithms for the analysis of emerging types of biological readouts, the potential for innovative ''in silico'' experiments, and freely available open code bases have helped to create opportunities for all research groups to contribute to both bioinformatics and the range of open-source software available, regardless of their funding arrangements. In order to maintain this tradition and create further opportunities, the non-profit Open Bioinformatics Foundation have supported the annual Bioinformatics Open Source Conference (BOSC) since 2000.<ref name="OBF-bosc">{{cite web \|url=http://www.open-bio.org/wiki/BOSC \|title=Open Bioinformatics Foundation: BOSC \|publisher=Open Bioinformatics Foundation \|accessdate=05 November 2013}}</ref>

	===Web services in bioinformatics===		===Web services in bioinformatics===
	SOAP and REST-based interfaces have been developed for a wide variety of bioinformatics applications allowing an application running on one computer in one part of the world to use algorithms, data and computing resources on servers in other parts of the world. The main advantages derive from the fact that end users do not have to deal with software and database maintenance overheads.

	Basic bioinformatics services are classified by the European Bioinformatics Institute\|EBI into ~~three~~ categories~~: SSS (Sequence Search Services)~~, ~~MSA (Multiple Sequence Alignment) and [[Bioinformatics#Sequence analysis\|BSA]] (Biological Sequence Analysis)~~. The availability of these service-oriented bioinformatics resources demonstrate the applicability of web based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single, standalone or web-based interface, to integrative, distributed and extensible bioinformatics workflow management systems.		SOAP and REST-based interfaces have been developed for a wide variety of bioinformatics applications, allowing an application running on one computer in one part of the world to use algorithms, data, and computing resources on servers in other parts of the world. The main advantages derive from the fact that end users do not have to deal with software and database maintenance overheads.

			Basic bioinformatics services are classified by the European Bioinformatics Institute (EBI) into numerous categories, including ontologies, structures, gene expression, proteins, etc. The availability of these service-oriented bioinformatics resources demonstrate the applicability of web-based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single, standalone, or web-based interface, to integrative, distributed, and extensible bioinformatics workflow management systems.<ref name="EBIAbout">{{cite web \|url=http://www.ebi.ac.uk/about \|title=Welcome to EMBL-EBI \|publisher=EMBL-EBI \|accessdate=05 November 2013}}</ref>

	==Further reading==		==Further reading==

Shawndouglas: Saved progress

2013-11-05T20:00:08Z

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Shawndouglas: /* History */

2013-11-05T00:51:16Z

History

← Older revision		Revision as of 00:51, 5 November 2013
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	==History==		==History==

	Arguably one of the first "bioinformatics" projects — though the concept didn't yet exist — involved the 1965 creation and maintenance of a protein sequence database called the ''Atlas of Protein Sequence and Structure'' by Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley. The work grew out of their "biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code."<ref name="EssBioInfo" /><ref name="CCCAtlas">{{cite journal \|url=http://www.ncbi.nlm.nih.gov/pubmed/20665074 \|journal=Journal of the History of Biology \|title=Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff’s ''Atlas of Protein Sequence and Structure'', 1954–1965 \|author=Strasser, Bruno J. \|volume=43 \|issue=4 \|pages=623–660 \|date=December 2010 \|pmid=20665074 \|doi=10.1007/s10739-009-9221-0}}</ref> Six years later the Brookhaven National Laboratory and the Cambridge Crystallographic Data Centre jointly created the Protein Data Bank, intended as a public database of three-dimensional protein structures. The work at Brookhaven would go on to influence others in the field to contribute, with 23 structures contributed in 1976, breaking 5,000 by the end of 1996 and 40,000 in 2006.<ref name="EssBioInfo" /><ref name="PDBHist">{{cite journal \|url=http://www.ebi.ac.uk/msd/embo08/pdf/pdb_history.pdf‎ \|format=PDF \|journal=Acta crystallographica. Section A, Foundations of crystallography \|title=The Protein Data Bank: a historical perspective \|author=Berman, Helen M. \|volume=64 \|issue=1 \|date=January 2008 \|pages=88–95 \|pmid=18156675}}</ref> The significant growth in contributions was fueled by several events, including: Peter Y. Chou and Gerald D. Fasman's 1974 creation (and later, refinement) of a protein structure prediction algorithm<ref name="ChouPred1">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1974 \|title=Prediction of protein conformation \|journal=Biochemistry \|volume=13 \|issue=2 \|pages=222–245 \|doi=10.1021/bi00699a002 \|pmid=4358940}}</ref><ref name="ChouPred2">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Empirical predictions of protein conformation \|journal=Annu Rev Biochem \|volume=47 \|pages=251–276 \|doi=10.1146/annurev.bi.47.070178.001343 \|pmid=354496}}</ref><ref name="ChouPred3">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Prediction of the secondary structure of proteins from their amino acid sequence \|journal=Adv Enzymol Relat Areas Mol Biol \|volume=47 \|pages=45–148 \|pmid=364941}}</ref>; David J. Lipman and William R. Pearson's 1985 development (and later, refinement) of FASTP (later FASTA)<ref name="RapSenProt">{{cite journal \|pmid=2983426 \|year=1985 \|title=Rapid and sensitive protein similarity searches \|volume=227 \|issue=4693 \|pages=1435–41 \|journal=Science \|doi=10.1126/science.2983426 \|author=Lipman, David J.; Pearson, William R.}}</ref><ref name="ImpToolBio">{{cite journal \|pmid=3162770 \|year=1988 \|title=Improved tools for biological sequence comparison \|volume=85 \|issue=8 \|pages=2444–8 \|pmc=280013 \|journal=Proceedings of the National Academy of Sciences of the United States of America \|doi=10.1073/pnas.85.8.2444 \|author=Lipman, David J.; Pearson, William R.}}</ref> as well as Stephen Altschul and company's 1990 development and refinement of BLAST<ref name="BLAST">{{cite journal \|author=Altschul, Stephen; Gish, Warren; Miller, Webb; Myers, Eugene; Lipman, David \|title=Basic local alignment search tool \|doi=10.1016/S0022-2836(05)80360-2 \|journal=Journal of Molecular Biology \|volume=215 \|issue=3 \|pages=403–410 \|year=1990 \|pmid=2231712}}</ref>, both database sequence searching algorithms and programs; and the formal start of the Human Genome Project in 1990.<ref name="EssBioInfo" />		Arguably one of the first "bioinformatics" projects — though the concept didn't yet exist — involved the 1965 creation and maintenance of a protein sequence database called the ''Atlas of Protein Sequence and Structure'' by Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley. The work grew out of their "biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code."<ref name="EssBioInfo" /><ref name="CCCAtlas">{{cite journal \|url=http://www.ncbi.nlm.nih.gov/pubmed/20665074 \|journal=Journal of the History of Biology \|title=Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff’s ''Atlas of Protein Sequence and Structure'', 1954–1965 \|author=Strasser, Bruno J. \|volume=43 \|issue=4 \|pages=623–660 \|date=December 2010 \|pmid=20665074 \|doi=10.1007/s10739-009-9221-0}}</ref> Six years later the Brookhaven National Laboratory and the Cambridge Crystallographic Data Centre jointly created the Protein Data Bank, intended as a public database of three-dimensional protein structures.

			The work at Brookhaven would go on to influence others in the field to contribute, with 23 structures contributed in 1976, breaking 5,000 by the end of 1996 and 40,000 in 2006.<ref name="EssBioInfo" /><ref name="PDBHist">{{cite journal \|url=http://www.ebi.ac.uk/msd/embo08/pdf/pdb_history.pdf‎ \|format=PDF \|journal=Acta crystallographica. Section A, Foundations of crystallography \|title=The Protein Data Bank: a historical perspective \|author=Berman, Helen M. \|volume=64 \|issue=1 \|date=January 2008 \|pages=88–95 \|pmid=18156675}}</ref> The significant growth in contributions was fueled by several events, including: Peter Y. Chou and Gerald D. Fasman's 1974 creation (and later, refinement) of a protein structure prediction algorithm<ref name="ChouPred1">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1974 \|title=Prediction of protein conformation \|journal=Biochemistry \|volume=13 \|issue=2 \|pages=222–245 \|doi=10.1021/bi00699a002 \|pmid=4358940}}</ref><ref name="ChouPred2">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Empirical predictions of protein conformation \|journal=Annu Rev Biochem \|volume=47 \|pages=251–276 \|doi=10.1146/annurev.bi.47.070178.001343 \|pmid=354496}}</ref><ref name="ChouPred3">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Prediction of the secondary structure of proteins from their amino acid sequence \|journal=Adv Enzymol Relat Areas Mol Biol \|volume=47 \|pages=45–148 \|pmid=364941}}</ref>; David J. Lipman and William R. Pearson's 1985 development (and later, refinement) of FASTP (later FASTA)<ref name="RapSenProt">{{cite journal \|pmid=2983426 \|year=1985 \|title=Rapid and sensitive protein similarity searches \|volume=227 \|issue=4693 \|pages=1435–41 \|journal=Science \|doi=10.1126/science.2983426 \|author=Lipman, David J.; Pearson, William R.}}</ref><ref name="ImpToolBio">{{cite journal \|pmid=3162770 \|year=1988 \|title=Improved tools for biological sequence comparison \|volume=85 \|issue=8 \|pages=2444–8 \|pmc=280013 \|journal=Proceedings of the National Academy of Sciences of the United States of America \|doi=10.1073/pnas.85.8.2444 \|author=Lipman, David J.; Pearson, William R.}}</ref> as well as Stephen Altschul and company's 1990 development and refinement of BLAST<ref name="BLAST">{{cite journal \|author=Altschul, Stephen; Gish, Warren; Miller, Webb; Myers, Eugene; Lipman, David \|title=Basic local alignment search tool \|doi=10.1016/S0022-2836(05)80360-2 \|journal=Journal of Molecular Biology \|volume=215 \|issue=3 \|pages=403–410 \|year=1990 \|pmid=2231712}}</ref>, both database sequence searching algorithms and programs; and the formal start of the Human Genome Project in 1990.<ref name="EssBioInfo" />

			A flurry of genome studies went on to produce unprecedented amounts of biological data, creating a sudden demand for rapid and efficient computational tools to manage and analyze the data. "The development of these computational tools depended on knowledge generated from a wide range of disciplines including mathematics, statistics, computer science, information technology, and molecular biology."<ref name="EssBioInfo" /> The merger of these disciplines largely went on to form what is now known as bioinformatics.


	In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:		In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:

Shawndouglas: Added more history.

2013-11-05T00:22:06Z

Added more history.

← Older revision		Revision as of 00:22, 5 November 2013
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	==History==		==History==

	Arguably one of the first "bioinformatics" projects — though the concept didn't yet exist — involved the 1965 creation and maintenance of a protein sequence database called the ''Atlas of Protein Sequence and Structure'' by Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley. The work grew out of their "biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code."<ref name="EssBioInfo" /><ref name="CCCAtlas">{{cite journal \|url=http://www.ncbi.nlm.nih.gov/pubmed/20665074 \|journal=Journal of the History of Biology \|title=Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff’s ''Atlas of Protein Sequence and Structure'', 1954–1965 \|author=Strasser, Bruno J. \|volume=43 \|issue=4 \|pages=623–660 \|date=December 2010 \|pmid=20665074 \|doi=10.1007/s10739-009-9221-0}}</ref> Six years later the Brookhaven National Laboratory and the Cambridge Crystallographic Data Centre jointly created the Protein Data Bank, intended as a public database of three-dimensional protein structures. The work at Brookhaven would go on to influence others in the field to contribute, with 23 structures contributed in 1976, breaking 5,000 by the end of 1996 and 40,000 in 2006.<ref name="EssBioInfo" /><ref name="PDBHist">{{cite journal \|url=http://www.ebi.ac.uk/msd/embo08/pdf/pdb_history.pdf‎ \|format=PDF \|journal=Acta crystallographica. Section A, Foundations of crystallography \|title=The Protein Data Bank: a historical perspective \|author=Berman, Helen M. \|volume=64 \|issue=1 \|date=January 2008 \|pages=88–95 \|pmid=18156675}}</ref> The significant growth in contributions was ~~partially~~ fueled by		Arguably one of the first "bioinformatics" projects — though the concept didn't yet exist — involved the 1965 creation and maintenance of a protein sequence database called the ''Atlas of Protein Sequence and Structure'' by Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley. The work grew out of their "biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code."<ref name="EssBioInfo" /><ref name="CCCAtlas">{{cite journal \|url=http://www.ncbi.nlm.nih.gov/pubmed/20665074 \|journal=Journal of the History of Biology \|title=Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff’s ''Atlas of Protein Sequence and Structure'', 1954–1965 \|author=Strasser, Bruno J. \|volume=43 \|issue=4 \|pages=623–660 \|date=December 2010 \|pmid=20665074 \|doi=10.1007/s10739-009-9221-0}}</ref> Six years later the Brookhaven National Laboratory and the Cambridge Crystallographic Data Centre jointly created the Protein Data Bank, intended as a public database of three-dimensional protein structures. The work at Brookhaven would go on to influence others in the field to contribute, with 23 structures contributed in 1976, breaking 5,000 by the end of 1996 and 40,000 in 2006.<ref name="EssBioInfo" /><ref name="PDBHist">{{cite journal \|url=http://www.ebi.ac.uk/msd/embo08/pdf/pdb_history.pdf‎ \|format=PDF \|journal=Acta crystallographica. Section A, Foundations of crystallography \|title=The Protein Data Bank: a historical perspective \|author=Berman, Helen M. \|volume=64 \|issue=1 \|date=January 2008 \|pages=88–95 \|pmid=18156675}}</ref> The significant growth in contributions was fueled by several events, including: Peter Y. Chou and Gerald D. Fasman's 1974 creation (and later, refinement) of a protein structure prediction algorithm<ref name="ChouPred1">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1974 \|title=Prediction of protein conformation \|journal=Biochemistry \|volume=13 \|issue=2 \|pages=222–245 \|doi=10.1021/bi00699a002 \|pmid=4358940}}</ref><ref name="ChouPred2">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Empirical predictions of protein conformation \|journal=Annu Rev Biochem \|volume=47 \|pages=251–276 \|doi=10.1146/annurev.bi.47.070178.001343 \|pmid=354496}}</ref><ref name="ChouPred3">{{cite journal \|author=Chou, Peter Y,; Fasman, Gerald D. \|year=1978 \|title=Prediction of the secondary structure of proteins from their amino acid sequence \|journal=Adv Enzymol Relat Areas Mol Biol \|volume=47 \|pages=45–148 \|pmid=364941}}</ref>; David J. Lipman and William R. Pearson's 1985 development (and later, refinement) of FASTP (later FASTA)<ref name="RapSenProt">{{cite journal \|pmid=2983426 \|year=1985 \|title=Rapid and sensitive protein similarity searches \|volume=227 \|issue=4693 \|pages=1435–41 \|journal=Science \|doi=10.1126/science.2983426 \|author=Lipman, David J.; Pearson, William R.}}</ref><ref name="ImpToolBio">{{cite journal \|pmid=3162770 \|year=1988 \|title=Improved tools for biological sequence comparison \|volume=85 \|issue=8 \|pages=2444–8 \|pmc=280013 \|journal=Proceedings of the National Academy of Sciences of the United States of America \|doi=10.1073/pnas.85.8.2444 \|author=Lipman, David J.; Pearson, William R.}}</ref> as well as Stephen Altschul and company's 1990 development and refinement of BLAST<ref name="BLAST">{{cite journal \|author=Altschul, Stephen; Gish, Warren; Miller, Webb; Myers, Eugene; Lipman, David \|title=Basic local alignment search tool \|doi=10.1016/S0022-2836(05)80360-2 \|journal=Journal of Molecular Biology \|volume=215 \|issue=3 \|pages=403–410 \|year=1990 \|pmid=2231712}}</ref>, both database sequence searching algorithms and programs; and the formal start of the Human Genome Project in 1990.<ref name="EssBioInfo" />






	In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:		In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:

Shawndouglas: Made some updates. Saving changes and adding more.

2013-11-04T23:48:05Z

Made some updates. Saving changes and adding more.

← Older revision		Revision as of 23:48, 4 November 2013
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	~~''(Article was taken from Wikipedia)''~~

	[[Image:Genome viewer screenshot small.png\|thumbnail\|right\|220px\|'''Map of the human X chromosome''' (from the NCBI website). Assembly of the human genome is one of the greatest achievements of bioinformatics.]]		[[Image:Genome viewer screenshot small.png\|thumbnail\|right\|220px\|'''Map of the human X chromosome''' (from the NCBI website). Assembly of the human genome is one of the greatest achievements of bioinformatics.]]

	'''Bioinformatics''' is the application of [[computer science]] and [[information technology]] to the field of biology.		'''Bioinformatics''' is the application of [[computer science]] and information technology to the field of biology, with a primary goal of understanding biological processes. What sets it apart from other approaches, however, is its focus on developing and applying computationally intensive techniques (e.g. pattern recognition, data mining, machine learning algorithms, and visualization) to achieve this goal. Major research efforts in the field include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression and protein–protein interactions, genome-wide association studies, and the modeling of evolution.<ref name="BioInfoPolanski">{{cite book \|url=http://books.google.com/books?id=oZbR3GEdmVMC \|title=Bioinformatics \|chapter=Chapter 1: Introduction \|author=Polanski, Andrzej \|publisher=Springer \|year=2007 \|pages=1–9 \|isbn=3540241663}}</ref><ref name="EssBioInfo">{{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|chapter=Chapter 1: Introduction \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=3–9 \|isbn=113945062X}}</ref>

	The ~~primary goal of~~ bioinformatics ~~is to increase~~ the ~~understanding~~ of ~~biological~~ processes. ~~What sets it apart from other approaches~~, ~~however~~, ~~is its focus on developing and applying computationally intensive techniques (e~~.g., [[~~pattern recognition~~]], ~~[[data mining]]~~, [[~~machine learning~~]] ~~algorithms,~~ and ~~visualization) to achieve this goal~~. ~~Major research efforts in~~ the ~~field include sequence alignment~~, ~~gene finding~~, ~~[[genome]] assembly~~, ~~[[drug design]], drug discovery, protein structure alignment, protein structure prediction, prediction of gene expression~~ and ~~protein–protein interactions, genome-wide association studies~~ and the ~~modeling~~ of ~~evolution~~.		The term "bioinformatics" was coined by Paulien Hogeweg and Ben Hesper in 1978 for "the study of informatic processes in biotic systems."<ref name="SimGrowth">{{cite journal \|url=http://bioinformatics.bio.uu.nl/pdf/Hogeweg78.pdf‎ \|format=PDF \|journal=Simulation \|title=Simulating the growth of cellular forms \|author=Hogeweg, Pauline \|volume=31 \|issue=3 \|pages=90–96 \|date=September 1978 \|doi=10.1177/003754977803100305}}</ref><ref name="RootsBio">{{cite journal \|url=http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002021 \|journal=PLOS Computational Biology \|title=The Roots of Bioinformatics in Theoretical Biology \|author=Hogeweg, Pauline \|volume=7 \|issue=3 \|date=31 March 2011 \|pmid=21483479 \|doi=10.1371/journal.pcbi.1002021}}</ref> Its primary use since at least the late 1980s has been in genomics and genetics, particularly in those areas of genomics involving large-scale [[DNA sequencing]]. However, rapid developments in genomic, molecular research, and information technologies have combined to produce a tremendous amount of [[information]] related to molecular and other types of biology. Bioinformatics now entails the creation and advancement of databases, algorithms, computational, and statistical techniques and theory to solve formal and practical problems arising from the management and analysis of biological data.

	~~The term ''~~bioinformatics~~'' was coined by Paulien Hogeweg~~ and Ben Hesper in 1978 for the study of informatic processes in biotic systems.<ref>{{cite doi\|10.1177/003754977803100305}}</ref><ref>{{cite pmid\|21483479}}</ref> Its primary use since at least the late 1980s has been in genomics and ~~genetics~~, ~~particularly in those areas~~ of ~~genomics involving large-scale [[DNA sequencing]]~~.		Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning different DNA and protein sequences to compare them, and creating and viewing 3-D models of protein structures.

	Bioinformatics now entails the creation and advancement of databases, algorithms, computational and statistical techniques and theory to solve formal and practical problems arising from the management and analysis of biological data.		==History==

	~~Over~~ the ~~past few decades rapid developments in genomic~~ and ~~other molecular research technologies~~ and ~~developments in information technologies have combined~~ to ~~produce~~ a ~~tremendous amount~~ of ~~[[information]] related~~ to ~~molecular biology. It is~~ the ~~name given~~ to ~~these mathematical~~ and ~~computing approaches used to glean understanding~~ of ~~biological processes~~.		Arguably one of the first "bioinformatics" projects — though the concept didn't yet exist — involved the 1965 creation and maintenance of a protein sequence database called the ''Atlas of Protein Sequence and Structure'' by Margaret O. Dayhoff, Richard V. Eck, and Robert S. Ledley. The work grew out of their "biochemical investigation of the relations between the structures and function of proteins and the theoretical attempt to decipher the genetic code."<ref name="EssBioInfo" /><ref name="CCCAtlas">{{cite journal \|url=http://www.ncbi.nlm.nih.gov/pubmed/20665074 \|journal=Journal of the History of Biology \|title=Collecting, Comparing, and Computing Sequences: The Making of Margaret O. Dayhoff’s ''Atlas of Protein Sequence and Structure'', 1954–1965 \|author=Strasser, Bruno J. \|volume=43 \|issue=4 \|pages=623–660 \|date=December 2010 \|pmid=20665074 \|doi=10.1007/s10739-009-9221-0}}</ref> Six years later the Brookhaven National Laboratory and the Cambridge Crystallographic Data Centre jointly created the Protein Data Bank, intended as a public database of three-dimensional protein structures. The work at Brookhaven would go on to influence others in the field to contribute, with 23 structures contributed in 1976, breaking 5,000 by the end of 1996 and 40,000 in 2006.<ref name="EssBioInfo" /><ref name="PDBHist">{{cite journal \|url=http://www.ebi.ac.uk/msd/embo08/pdf/pdb_history.pdf‎ \|format=PDF \|journal=Acta crystallographica. Section A, Foundations of crystallography \|title=The Protein Data Bank: a historical perspective \|author=Berman, Helen M. \|volume=64 \|issue=1 \|date=January 2008 \|pages=88–95 \|pmid=18156675}}</ref> The significant growth in contributions was partially fueled by

	Common activities in bioinformatics include mapping and analyzing DNA and protein sequences, aligning different DNA and protein sequences to compare them and creating and viewing 3-D models of protein structures.



	~~==Introduction==~~
	Bioinformatics was applied in the creation and maintenance of a database to store biological information at the beginning of the "genomic revolution", such as nucleotide and amino acid sequences. Development of this type of database involved not only design issues but the development of complex interfaces whereby researchers could both access existing data as well as submit new or revised data.

	In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:		In order to study how normal cellular activities are altered in different disease states, the biological data must be combined to form a comprehensive picture of these activities. Therefore, the field of bioinformatics has evolved such that the most pressing task now involves the analysis and interpretation of various types of data, including nucleotide and amino acid sequences, protein domains, and protein structures. The actual process of analyzing and interpreting data is referred to as computational biology. Important sub-disciplines within bioinformatics and computational biology include:
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	Basic bioinformatics services are classified by the European Bioinformatics Institute\|EBI into three categories: SSS (Sequence Search Services), MSA (Multiple Sequence Alignment) and [[Bioinformatics#Sequence analysis\|BSA]] (Biological Sequence Analysis). The availability of these service-oriented bioinformatics resources demonstrate the applicability of web based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single, standalone or web-based interface, to integrative, distributed and extensible bioinformatics workflow management systems.		Basic bioinformatics services are classified by the European Bioinformatics Institute\|EBI into three categories: SSS (Sequence Search Services), MSA (Multiple Sequence Alignment) and [[Bioinformatics#Sequence analysis\|BSA]] (Biological Sequence Analysis). The availability of these service-oriented bioinformatics resources demonstrate the applicability of web based bioinformatics solutions, and range from a collection of standalone tools with a common data format under a single, standalone or web-based interface, to integrative, distributed and extensible bioinformatics workflow management systems.

	~~==See also==~~

	~~==References==~~
	~~<references/>~~

	==Further reading==		==Further reading==
	~~<!-- It's possible that some of these were used as the original sources for the article. -->~~
	* Achuthsankar S Nair [http://print.achuth.googlepages.com/BINFTutorialV5.0CSI07.pdf Computational Biology & Bioinformatics – A gentle Overview], Communications of Computer Society of India, January 2007
	* Aluru, Srinivas, ed. ''Handbook of Computational Molecular Biology''. Chapman & Hall/Crc, 2006. ISBN 1584884061 (Chapman & Hall/Crc Computer and Information Science Series)
	* Baldi, P and Brunak, S, ''Bioinformatics: The Machine Learning Approach'', 2nd edition. MIT Press, 2001. ISBN 0-262-02506-X
	* Barnes, M.R. and Gray, I.C., eds., ''Bioinformatics for Geneticists'', first edition. Wiley, 2003. ISBN 0-470-84394-2
	* Baxevanis, A.D. and Ouellette, B.F.F., eds., ''Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins'', third edition. Wiley, 2005. ISBN 0-471-47878-4
	* Baxevanis, A.D., Petsko, G.A., Stein, L.D., and Stormo, G.D., eds., ''Current Protocols in Bioinformatics''. Wiley, 2007. ISBN 0-471-25093-7
	* Claverie, J.M. and C. Notredame, ''Bioinformatics for Dummies''. Wiley, 2003. ISBN 0-7645-1696-5
	* Cristianini, N. and Hahn, M. [http://www.computational-genomics.net/ ''Introduction to Computational Genomics''], Cambridge University Press, 2006. (ISBN 9780521671910 \| ISBN 0521671914)
	* Durbin, R., S. Eddy, A. Krogh and G. Mitchison, ''Biological sequence analysis''. Cambridge University Press, 1998. ISBN 0-521-62971-3
	* Gilbert, D. [http://bib.oxfordjournals.org/cgi/content/abstract/5/3/300 ''Bioinformatics software resources'']. Briefings in Bioinformatics, Briefings in Bioinformatics, 2004 5(3):300–304.
	* Keedwell, E., ''Intelligent Bioinformatics: The Application of Artificial Intelligence Techniques to Bioinformatics Problems''. Wiley, 2005. ISBN 0-470-02175-6
	* Kohane, et al. ''Microarrays for an Integrative Genomics.'' The MIT Press, 2002. ISBN 0-262-11271-X
	* Lund, O. et al. ''Immunological Bioinformatics.'' The MIT Press, 2005. ISBN 0-262-12280-4
	* Michael S. Waterman, ''Introduction to Computational Biology: Sequences, Maps and Genomes''. CRC Press, 1995. ISBN 0-412-99391-0
	* Mount, David W. ''Bioinformatics: Sequence and Genome Analysis'' Spring Harbor Press, May 2002. ISBN 0-87969-608-7
	* Pachter, Lior and Sturmfels, Bernd. "Algebraic Statistics for Computational Biology" Cambridge University Press, 2005. ISBN 0-521-85700-7
	* Pevzner, Pavel A. ''Computational Molecular Biology: An Algorithmic Approach'' The MIT Press, 2000. ISBN 0-262-16197-4
	* Soinov, L. [http://jprr.org/index.php/jprr/article/view/8/5 Bioinformatics and Pattern Recognition Come Together] Journal of Pattern Recognition Research ([http://www.jprr.org JPRR]), Vol 1 (1) 2006 p. 37–41
	* Tisdall, James. "Beginning Perl for Bioinformatics" O'Reilly, 2001. ISBN 0-596-00080-4
	* [http://publishing.royalsociety.org/bioinformatics Dedicated issue of ''Philosophical Transactions B'' on Bioinformatics freely available]
	* [http://www.nap.edu/catalog/11480.html Catalyzing Inquiry at the Interface of Computing and Biology (2005) CSTB report]
	* [http://www.nap.edu/catalog/2121.html Calculating the Secrets of Life: Contributions of the Mathematical Sciences and computing to Molecular Biology (1995)]
	* [http://ocw.mit.edu/OcwWeb/Biology/7-91JSpring2004/LectureNotes/index.htm Foundations of Computational and Systems Biology MIT Course]
	* [http://compbio.mit.edu/6.047/ Computational Biology: Genomes, Networks, Evolution Free MIT Course]
	* [http://ocw.mit.edu/OcwWeb/Electrical-Engineering-and-Computer-Science/6-096Spring-2005/CourseHome/index.htm Algorithms for Computational Biology Free MIT Course]
	* [http://www.ncbi.nlm.nih.gov/pubmed/18842678 Zhang, Z., Cheung, K.H. and Townsend, J.P. Bringing Web 2.0 to bioinformatics, Briefing in Bioinformatics. In press]

			* {{cite book \|url=http://books.google.com/books?id=p_qzpkNVcUwC \|title=An Introduction to Bioinformatics Algorithms \|author=Jones, Neil C.; Pevzner, Pavel A. \|publisher=MIT Press \|year=2004 \|pages=435 \|isbn=0262101068}}
			* {{cite book \|url=http://books.google.com/books?id=et5qQgAACAAJ \|title=Introduction to Bioinformatics \|author=Lesk, Arthur \|publisher=OUP Oxford \|year=2008 \|pages=474 \|edition=3rd \|isbn=0199208042}}
			* {{cite book \|url=http://books.google.com/books?id=AFsu7_goA8kC \|title=Essential Bioinformatics \|author=Xiong, Jin \|publisher=Cambridge University Press \|year=2006 \|pages=339 \|isbn=113945062X}}

	==External links==		==External links==
	<!-- Please use the talk page to propose any additions to this section. If you do not do this, the link will almost certainly be deleted. Also, do not list bioinformatics research groups or centers.-->		<!-- Please use the talk page to propose any additions to this section. If you do not do this, the link will almost certainly be deleted. Also, do not list bioinformatics research groups or centers.-->
	* [http://bioinformatics.org/ Bioinformatics Organization]		* [http://www.bioinformatics.org/ The Bioinformatics Organization]
	* [http://www.google.com/Top/Science/Biology/Bioinformatics/Research_Groups/ Bioinformatics Research Groups]		* [http://www.embnet.org/ Bioinformatics Without Borders]
	* [http://www.embnet.org/ ~~EMBnet~~]
	* [http://www.open-bio.org/ Open Bioinformatics Foundation]		* [http://www.open-bio.org/ Open Bioinformatics Foundation]

			==References==
			<references/>

	[[Category:Informatics]]		[[Category:Informatics]]