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Title:
Homology-based inference sets the bar high for protein function prediction | BMC Bioinformatics
Description:
Background Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference. Methods Here, we describe a few methods that predict protein function exclusively through homology. Together, they set the bar or lower limit for future improvements. Results and conclusions During the development of these methods, we faced two surprises. Firstly, our most successful implementation for the baseline ranked very high at CAFA1. In fact, our best combination of homology-based methods fared only slightly worse than the top-of-the-line prediction method from the Jones group. Secondly, although the concept of homology-based inference is simple, this work revealed that the precise details of the implementation are crucial: not only did the methods span from top to bottom performers at CAFA, but also the reasons for these differences were unexpected. In this work, we also propose a new rigorous measure to compare predicted and experimental annotations. It puts more emphasis on the details of protein function than the other measures employed by CAFA and may best reflect the expectations of users. Clearly, the definition of proper goals remains one major objective for CAFA.
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Keywords {🔍}
methods, terms, cafa, threshold, measure, leaf, term, protein, prediction, function, score, method, priors, annotations, predicted, set, top, article, psiblast, figure, proteins, recall, experimental, hits, pubmed, annotation, data, predictions, bpo, precision, blast, performance, google, scholar, measures, mfo, leaves, swissprot, homologybased, number, postcafa, gotcha, reliability, target, inference, baseline, scores, table, studenta, ontology,
Topics {✒️}
biological process ontology marti-renom ma florian auer rule-based protein annotator homology-based inference sets /bmcbioinformatics/supplements/14/s3 simple homology-based inference biological process membrane protein structure open access article article number s7 functional keywords diverse nearest-neighbor methods k-nearest-neighbor approach basic homology-inference methods maintaining excellent databases article download pdf homology-based methods fared meta classifier [13] single-function aldolase enzyme returned psi-blast e-values homology-based inference predict protein function homology-based method ranks author information authors post-cafa parameter optimization full size image random swiss-prot protein nearest-neighbor principles protein function assessed optimization process protein function prediction protein function prediction typical swiss-prot annotations multiple psi-blast hits privacy choices/manage cookies entire psi-blast query imply high accuracy/precision nucleic acids research artificial intelligence research homology-based methods homology-based predictors molecular function ontology post-cafa optimization baseline background full size table universal protein resource author correspondence cellular component ontology top psi-blast hits
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headline:Homology-based inference sets the bar high for protein function prediction
description:Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference. Here, we describe a few methods that predict protein function exclusively through homology. Together, they set the bar or lower limit for future improvements. During the development of these methods, we faced two surprises. Firstly, our most successful implementation for the baseline ranked very high at CAFA1. In fact, our best combination of homology-based methods fared only slightly worse than the top-of-the-line prediction method from the Jones group. Secondly, although the concept of homology-based inference is simple, this work revealed that the precise details of the implementation are crucial: not only did the methods span from top to bottom performers at CAFA, but also the reasons for these differences were unexpected. In this work, we also propose a new rigorous measure to compare predicted and experimental annotations. It puts more emphasis on the details of protein function than the other measures employed by CAFA and may best reflect the expectations of users. Clearly, the definition of proper goals remains one major objective for CAFA.
datePublished:2013-02-28T00:00:00Z
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Experimental Annotation
Predict Protein Function
Biological Process Ontology
Baseline Classifier
Bioinformatics
Microarrays
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Algorithms
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headline:Homology-based inference sets the bar high for protein function prediction
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Experimental Annotation
Predict Protein Function
Biological Process Ontology
Baseline Classifier
Bioinformatics
Microarrays
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Algorithms
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type:PostalAddress
type:Organization
name:Maximilian Hecht
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Mark Heron
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Peter Hönigschmid
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Thomas A Hopf
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Stefanie Kaufmann
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Michael Kiening
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Denis Krompass
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Cedric Landerer
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Yannick Mahlich
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Manfred Roos
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Burkhard Rost
affiliation:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology
address:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:Institute of Advanced Study (TUM-IAS) Lichtenbergstr. 2a
address:
name:Institute of Advanced Study (TUM-IAS) Lichtenbergstr. 2a, Garching/Munich, Germany
type:PostalAddress
type:Organization
name:New York Consortium on Membrane Protein Structure (NYCOMPS) & Department of Biochemistry and Molecular Biophysics Columbia University
address:
name:New York Consortium on Membrane Protein Structure (NYCOMPS) & Department of Biochemistry and Molecular Biophysics Columbia University, New York, USA
type:PostalAddress
type:Organization
email:[email protected]
PostalAddress:
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:TUM, Department of Informatics, Bioinformatics & Computational Biology, Garching/Munich, Germany
name:Institute of Advanced Study (TUM-IAS) Lichtenbergstr. 2a, Garching/Munich, Germany
name:New York Consortium on Membrane Protein Structure (NYCOMPS) & Department of Biochemistry and Molecular Biophysics Columbia University, New York, USA
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