Difference between revisions of "Template:Article of the week"

From LIMSWiki
Jump to navigationJump to search
m (Spacing)
(Updated article of the week text)
(434 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:1FYT T-cell receptor and HLA class II complex.png|140px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''[[Immunoinformatics]]''' (sometimes referred to as '''computational immunology''') is a sub-branch of [[bioinformatics]] that focuses on the use of data management and computational tools to improve immunological research. The scope of immunoinformatics covers a wide variety of territory, from genomic and proteomic study of the immune system to molecular- and organism-level modeling, putting it in close ties with [[genome informatics]].
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Immunology researchers like Hans-Georg Rammensee trace the history of immunoinformatics back to the study of theoretical immunology. In June 1987, the Theoretical Immunology Workshop was hosted in Santa Fe, New Mexico to discuss "the topics of immune surveillance, mathematical models of HIV infection, complexities of antigen-antibody systems, immune suppression and tolerance, and idiotypie networks." One of the first immunoinformatics efforts to result in a long-term informatics solution was the construction of the IMGT information system in 1989 by the Laboratoire d'ImmunoGénétique Moléculaire (LIGM). Created to "standardize and manage the complexity of the immunogenetics data" coming out of the lab, the information system went on to become an international public reference for genetic and proteomic data related to immunology. ('''[[Immunoinformatics|Full article...]]''')<br />
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />


<br />
''Recently featured'':
''Recently featured'': [[Life sciences industry]], [[Chemical industry]], [[Skilled nursing facility]]
{{flowlist |
* [[Journal:Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology|Hierarchical AI enables global interpretation of culture plates in the era of digital microbiology]]
* [[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]
* [[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]
}}

Revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

Recently featured:

Retrieved from "https://www.limswiki.org/index.php?title=Template:Article_of_the_week&oldid=64398"