↓ Skip to main content
What is this page? Embed badge

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
  8. Altmetric Badge
    Chapter 7 The ProFunc Function Prediction Server
  9. Altmetric Badge
    Chapter 8 G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures
  10. Altmetric Badge
    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
  12. Altmetric Badge
    Chapter 11 Enzyme Annotation and Metabolic Reconstruction Using KEGG
  13. Altmetric Badge
    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 6: Predicting Secretory Proteins with SignalP
Altmetric Badge

Citations

dimensions_citation
26 Dimensions

Readers on

mendeley
536 Mendeley
Summary Dimensions citations
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Predicting Secretory Proteins with SignalP
Chapter number 6
Book title
Protein Function Prediction
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-7015-5_6
Pubmed ID
28451972
Book ISBNs
978-1-4939-7013-1, 978-1-4939-7015-5
Authors

Henrik Nielsen, Nielsen, Henrik

Editors

Daisuke Kihara

Abstract

SignalP is the currently most widely used program for prediction of signal peptides from amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway, but are not necessarily secreted. After a brief introduction to the biology of signal peptides and the history of signal peptide prediction, this chapter will describe all the options of the current version of SignalP and the details of the output from the program. The chapter includes a case study where the scores of SignalP were used in a novel way to predict the functional effects of amino acid substitutions in signal peptides.

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 536 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 536 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 116 22%
Student > Master 79 15%
Student > Bachelor 69 13%
Researcher 68 13%
Student > Doctoral Student 22 4%
Other 59 11%
Unknown 123 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 179 33%
Agricultural and Biological Sciences 134 25%
Immunology and Microbiology 25 5%
Environmental Science 8 1%
Medicine and Dentistry 7 1%
Other 41 8%
Unknown 142 26%

This page is provided by Altmetric.