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Title:
Community-Wide Evaluation of Computational Function Prediction | SpringerLink
Description:
A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights...
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Keywords {🔍}

cafa, function, methods, protein, prediction, terms, ontology, google, scholar, data, annotation, challenge, gene, proteins, information, computational, experimental, pubmed, evaluation, time, set, annotations, performance, term, article, molecular, functional, predicted, content, biological, provide, method, recall, chapter, assessment, metrics, precision, sequence, community, number, predictions, biology, bioinformatics, organizers, fig, evidence, nodes, cas, research, friedberg,

Topics {✒️}

}{\mathrm{max}}\left\{2\times \frac{\mathrm{pr} mathrm{\hspace{1em}}\phantom{\rule{0 structured-output learning perspective machine learning expertise machine learning challenges 25em}{0ex}}\phantom{\rule{0 }\mathrm{log}}\mathrm{pr} 25em}{0ex}}\mathrm{mi} }_{\mathrm{max}}=\underset{ 25em}{0ex}}\mathrm{rc} high-quality systems data open access chapter }_{\mathrm{min}}=\underset{ ru-mi space depends ongoing community-wide challenge high-throughput sequencing privacy choices/manage cookies protein/protein interaction data include “dna binding” open access license evaluating ontology-based predictions times \mathrm{rc} swiss-prot database enabled macromolecular interactions [21 key residues remaining uncertainty-misinformation curves gene ontology handbook accessible computing platforms gene function prediction computational function prediction computational evidence codes high-throughput experiments amino acid sequence protein function prediction protein function prediction function prediction program developing assessment rules protein function space community-wide evaluation community-wide effort false-positive prediction =-{\displaystyle \sum _{ term “dna binding” molecular function category protein function annotators experimental evidence codes st onge rp high throughput means dna-binding proteins gene ontology consortium

Questions {❓}

) The following question arises: if we know that the protein is annotated with the term “Nucleic acid binding,” how can we quantify the additional information provided by the term “DNA binding” or incorrect information provided by the term “RNA binding”?
First, what makes a good prediction?
Stephens ZD, Lee SY, Faghri F, Campbell RH, Zhai C, Efron MJ, Iyer R, Schatz MC, Sinha S, Robinson GE (2015) Big data: astronomical or genomical?

Schema {🗺️}

ScholarlyArticle:
      headline:Community-Wide Evaluation of Computational Function Prediction
      pageEnd:146
      pageStart:133
      image:https://media.springernature.com/w153/springer-static/cover/book/978-1-4939-3743-1.jpg
      genre:
         Springer Protocols
      isPartOf:
         name:The Gene Ontology Handbook
         isbn:
            978-1-4939-3743-1
            978-1-4939-3741-7
         type:Book
      publisher:
         name:Springer New York
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:Iddo Friedberg
            affiliation:
                  name:Iowa State University
                  address:
                     name:Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Predrag Radivojac
            affiliation:
                  name:Indiana University
                  address:
                     name:Department of Computer Science and Informatics, Indiana University, Bloomington, USA
                     type:PostalAddress
                  type:Organization
            type:Person
      keywords:Function prediction, Algorithms, Evaluation, Machine learning
      description:A biological experiment is the most reliable way of assigning function to a protein. However, in the era of high-throughput sequencing, scientists are unable to carry out experiments to determine the function of every single gene product. Therefore, to gain insights into the activity of these molecules and guide experiments, we must rely on computational means to functionally annotate the majority of sequence data. To understand how well these algorithms perform, we have established a challenge involving a broad scientific community in which we evaluate different annotation methods according to their ability to predict the associations between previously unannotated protein sequences and Gene Ontology terms. Here we discuss the rationale, benefits, and issues associated with evaluating computational methods in an ongoing community-wide challenge.
      datePublished:2017
      isAccessibleForFree:1
      context:https://schema.org
Book:
      name:The Gene Ontology Handbook
      isbn:
         978-1-4939-3743-1
         978-1-4939-3741-7
Organization:
      name:Springer New York
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:Iowa State University
      address:
         name:Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, USA
         type:PostalAddress
      name:Indiana University
      address:
         name:Department of Computer Science and Informatics, Indiana University, Bloomington, USA
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:Iddo Friedberg
      affiliation:
            name:Iowa State University
            address:
               name:Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, USA
               type:PostalAddress
            type:Organization
      name:Predrag Radivojac
      affiliation:
            name:Indiana University
            address:
               name:Department of Computer Science and Informatics, Indiana University, Bloomington, USA
               type:PostalAddress
            type:Organization
PostalAddress:
      name:Department of Veterinary Microbiology and Preventive Medicine, Iowa State University, Ames, USA
      name:Department of Computer Science and Informatics, Indiana University, Bloomington, USA

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