Literature DB >> 27473066

Gene Ontology semantic similarity tools: survey on features and challenges for biological knowledge discovery.

Gaston K Mazandu, Emile R Chimusa, Nicola J Mulder.   

Abstract

Gene Ontology (GO) semantic similarity tools enable retrieval of semantic similarity scores, which incorporate biological knowledge embedded in the GO structure for comparing or classifying different proteins or list of proteins based on their GO annotations. This facilitates a better understanding of biological phenomena underlying the corresponding experiment and enables the identification of processes pertinent to different biological conditions. Currently, about 14 tools are available, which may play an important role in improving protein analyses at the functional level using different GO semantic similarity measures. Here we survey these tools to provide a comprehensive view of the challenges and advances made in this area to avoid redundant effort in developing features that already exist, or implementing ideas already proven to be obsolete in the context of GO. This helps researchers, tool developers, as well as end users, understand the underlying semantic similarity measures implemented through knowledge of pertinent features of, and issues related to, a particular tool. This should empower users to make appropriate choices for their biological applications and ensure effective knowledge discovery based on GO annotations.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Keywords:  Gene Ontology annotations; gene ontology; protein functional analysis; protein functional similarity; semantic similarity tools

Mesh:

Year:  2017        PMID: 27473066     DOI: 10.1093/bib/bbw067

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  22 in total

1.  Sub-GOFA: A tool for Sub-Gene Ontology function analysis in clonal mosaicism using semantic (logical) similarity.

Authors:  Tadaaki Katsuda; Noriko Sato; Kaoru Mogushi; Takeshi Hase; Masaaki Muramatsu
Journal:  Bioinformation       Date:  2022-01-31

2.  Semantic similarity and machine learning with ontologies.

Authors:  Maxat Kulmanov; Fatima Zohra Smaili; Xin Gao; Robert Hoehndorf
Journal:  Brief Bioinform       Date:  2021-07-20       Impact factor: 11.622

3.  The effects of shared information on semantic calculations in the gene ontology.

Authors:  Paul W Bible; Hong-Wei Sun; Maria I Morasso; Rasiah Loganantharaj; Lai Wei
Journal:  Comput Struct Biotechnol J       Date:  2017-01-30       Impact factor: 7.271

4.  A post-gene silencing bioinformatics protocol for plant-defence gene validation and underlying process identification: case study of the Arabidopsis thaliana NPR1.

Authors:  Rosita E Yocgo; Ephifania Geza; Emile R Chimusa; Gaston K Mazandu
Journal:  BMC Plant Biol       Date:  2017-11-23       Impact factor: 4.215

5.  Identifying term relations cross different gene ontology categories.

Authors:  Jiajie Peng; Honggang Wang; Junya Lu; Weiwei Hui; Yadong Wang; Xuequn Shang
Journal:  BMC Bioinformatics       Date:  2017-12-28       Impact factor: 3.169

6.  Refine gene functional similarity network based on interaction networks.

Authors:  Zhen Tian; Maozu Guo; Chunyu Wang; Xiaoyan Liu; Shiming Wang
Journal:  BMC Bioinformatics       Date:  2017-12-28       Impact factor: 3.169

7.  Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach.

Authors:  Jiajie Peng; Xuanshuo Zhang; Weiwei Hui; Junya Lu; Qianqian Li; Shuhui Liu; Xuequn Shang
Journal:  BMC Syst Biol       Date:  2018-03-19

8.  Virus-Host Interaction Gets Curiouser and Curiouser. PART II: Functional Transcriptomics of the E. coli DksA-Deficient Cell upon Phage P1vir Infection.

Authors:  Grzegorz M Cech; Agnieszka Szalewska-Pałasz; Katarzyna Potrykus; Anna Kloska
Journal:  Int J Mol Sci       Date:  2021-06-07       Impact factor: 5.923

9.  An improved approach to infer protein-protein interaction based on a hierarchical vector space model.

Authors:  Jiongmin Zhang; Ke Jia; Jinmeng Jia; Ying Qian
Journal:  BMC Bioinformatics       Date:  2018-04-27       Impact factor: 3.169

Review 10.  Role of the early secretory pathway in SARS-CoV-2 infection.

Authors:  Daria Sicari; Aristotelis Chatziioannou; Theodoros Koutsandreas; Roberto Sitia; Eric Chevet
Journal:  J Cell Biol       Date:  2020-09-07       Impact factor: 8.077

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