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Protein Function Prediction

Overview of attention for book
Cover of 'Protein Function Prediction'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Using PFP and ESG Protein Function Prediction Web Servers
  3. Altmetric Badge
    Chapter 2 GHOSTX: A Fast Sequence Homology Search Tool for Functional Annotation of Metagenomic Data
  4. Altmetric Badge
    Chapter 3 From Gene Annotation to Function Prediction for Metagenomics
  5. Altmetric Badge
    Chapter 4 An Agile Functional Analysis of Metagenomic Data Using SUPER-FOCUS
  6. Altmetric Badge
    Chapter 5 MPFit: Computational Tool for Predicting Moonlighting Proteins
  7. Altmetric Badge
    Chapter 6 Predicting Secretory Proteins with SignalP
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    Chapter 7 The ProFunc Function Prediction Server
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    Chapter 8 G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures
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    Chapter 9 Local Alignment of Ligand Binding Sites in Proteins for Polypharmacology and Drug Repositioning
  11. Altmetric Badge
    Chapter 10 WATsite2.0 with PyMOL Plugin: Hydration Site Prediction and Visualization
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    Chapter 11 Enzyme Annotation and Metabolic Reconstruction Using KEGG
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    Chapter 12 Ortholog Identification and Comparative Analysis of Microbial Genomes Using MBGD and RECOG
  14. Altmetric Badge
    Chapter 13 Exploring Protein Function Using the Saccharomyces Genome Database
  15. Altmetric Badge
    Chapter 14 Network-Based Gene Function Prediction in Mouse and Other Model Vertebrates Using MouseNet Server
  16. Altmetric Badge
    Chapter 15 The FANTOM5 Computation Ecosystem: Genomic Information Hub for Promoters and Active Enhancers
  17. Altmetric Badge
    Chapter 16 Multi-Algorithm Particle Simulations with Spatiocyte
Attention for Chapter 9: Local Alignment of Ligand Binding Sites in Proteins for Polypharmacology and Drug Repositioning
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Chapter title
Local Alignment of Ligand Binding Sites in Proteins for Polypharmacology and Drug Repositioning
Chapter number 9
Book title
Protein Function Prediction
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-7015-5_9
Pubmed ID
28451975
Book ISBNs
978-1-4939-7013-1, 978-1-4939-7015-5
Authors

Michal Brylinski

Editors

Daisuke Kihara

Abstract

The administration of drugs is a key strategy in pharmacotherapy to treat diseases. Drugs are typically developed to modulate the function of specific proteins, which are directly associated with particular disease states. Nonetheless, recent studies suggest that protein-drug interactions are rather promiscuous and the majority of pharmaceuticals exhibit activity against multiple, often unrelated proteins. Certainly, the lack of selectivity often leads to drug side effects; on the other hand, these polypharmacological attributes can be used to develop drugs acting on multiple targets within a unique disease pathway, as well as to identify new targets for existing drugs, which is known as drug repositioning. To support drug development and repurposing, we developed eMatchSite, a new approach to detect those binding sites having the capability to bind similar compounds. eMatchSite is available as a standalone software and a webserver at http://www.brylinski.org/ematchsite .

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 16%
Researcher 2 11%
Student > Bachelor 1 5%
Professor 1 5%
Student > Doctoral Student 1 5%
Other 4 21%
Unknown 7 37%
Readers by discipline Count As %
Chemistry 2 11%
Medicine and Dentistry 2 11%
Environmental Science 1 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Agricultural and Biological Sciences 1 5%
Other 3 16%
Unknown 9 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 May 2017.
All research outputs
#18,546,002
of 22,968,808 outputs
Outputs from Methods in molecular biology
#7,935
of 13,137 outputs
Outputs of similar age
#236,093
of 310,521 outputs
Outputs of similar age from Methods in molecular biology
#182
of 278 outputs
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So far Altmetric has tracked 13,137 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 278 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.

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