Enabling full‐length evolutionary profiles based deep convolutional neural network for predicting DNA‐binding proteins from sequence-Reference-Cited by-同舟云学术

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Enabling full‐length evolutionary profiles based deep convolutional neural network for predicting DNA‐binding proteins from sequence

Published:2019-07-08 Issue:1 Volume:88 Page:15-30
ISSN:0887-3585
Container-title:Proteins: Structure, Function, and Bioinformatics
language:en
Short-container-title:Proteins

Author:

Chauhan Sucheta¹,Ahmad Shandar¹^ORCID

Affiliation:

1. School of Computational and Integrative SciencesJawaharlal Nehru University New Delhi India

Funder

Bangladesh Council of Scientific and Industrial Research

Department of Biotechnology , Ministry of Science and Technology

Department of Science and Technology, Ministry of Science and Technology

Science and Engineering Research Board

Publisher

Wiley

Subject

Molecular Biology,Biochemistry,Structural Biology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/prot.25763

Reference69 articles.

1. HFSP: high speed homology-driven function annotation of proteins

2. Biases in the Experimental Annotations of Protein Function and Their Effect on Our Understanding of Protein Function Space

3. Protein function annotation by homology-based inference

4. Understanding how and why the Gene Ontology and its annotations evolve: the GO within UniProt

5. Spaced words and kmacs: fast alignment-free sequence comparison based on inexact word matches

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