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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:GA Terlouw JofCheminfo22 14.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:PIKAChU: A Python-based informatics kit for analyzing chemical units|PIKAChU: A Python-based informatics kit for analyzing chemical units]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|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 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 />


As efforts to computationally describe and simulate the biochemical world become more commonplace, computer programs that are capable of ''in silico'' chemistry play an increasingly important role in biochemical research. While such programs exist, they are often dependency-heavy, difficult to navigate, or not written in [[Python (programming language)|Python]], the programming language of choice for [[Bioinformatics|bioinformaticians]]. Here, we introduce PIKAChU (Python-based Informatics Kit for Analysing CHemical Units), a [[Chemical informatics|cheminformatics]] toolbox with few dependencies implemented in Python. PIKAChU builds comprehensive molecular graphs from simplified molecular-input line-entry system (SMILES) strings, which allow for easy downstream analysis and visualization of molecules. ... ('''[[Journal:PIKAChU: A Python-based informatics kit for analyzing chemical units|Full article...]]''')<br />
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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...)

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