0000000000389023

AUTHOR

John M. Hancock

0000-0003-2991-2217

showing 2 related works from this author

Disentangling the complexity of low complexity proteins

2020

Abstract There are multiple definitions for low complexity regions (LCRs) in protein sequences, with all of them broadly considering LCRs as regions with fewer amino acid types compared to an average composition. Following this view, LCRs can also be defined as regions showing composition bias. In this critical review, we focus on the definition of sequence complexity of LCRs and their connection with structure. We present statistics and methodological approaches that measure low complexity (LC) and related sequence properties. Composition bias is often associated with LC and disorder, but repeats, while compositionally biased, might also induce ordered structures. We illustrate this dichot…

Protein ConformationComputer scienceReview ArticleComputational biologyMeasure (mathematics)Evolution MolecularLow complexity03 medical and health sciencesProtein DomainsAmino Acid Sequencestructure[SDV.BBM.BC]Life Sciences [q-bio]/Biochemistry Molecular Biology/Biochemistry [q-bio.BM]Databases ProteinMolecular Biology030304 developmental biologyStructure (mathematical logic)0303 health sciencesSequence[SCCO.NEUR]Cognitive science/Neurosciencecomposition bias030302 biochemistry & molecular biologyProteinsdisorderlow complexity regionsStructure and function[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]AlgorithmsInformation SystemsBriefings in Bioinformatics
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PlaToLoCo: the first web meta-server for visualization and annotation of low complexity regions in proteins

2020

Abstract Low complexity regions (LCRs) in protein sequences are characterized by a less diverse amino acid composition compared to typically observed sequence diversity. Recent studies have shown that LCRs may co-occur with intrinsically disordered regions, are highly conserved in many organisms, and often play important roles in protein functions and in diseases. In previous decades, several methods have been developed to identify regions with LCRs or amino acid bias, but most of them as stand-alone applications and currently there is no web-based tool which allows users to explore LCRs in protein sequences with additional functional annotations. We aim to fill this gap by providing PlaToL…

Sequence analysisAcademicSubjects/SCI00010Protein domainComputational biologyBiologyDomain (software engineering)Computer graphics03 medical and health sciencesAnnotationProtein DomainsSequence Analysis ProteinGeneticsComputer GraphicsHumansAmino Acids030304 developmental biology0303 health sciencesIntersection (set theory)030302 biochemistry & molecular biologyMembrane ProteinsProteinsMolecular Sequence AnnotationVisualizationMolecular Sequence AnnotationWeb Server IssueSoftwareNucleic Acids Research
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