Literature DB >> 12715834

Bioinformatics for venom and toxin sciences.

Paul T J Tan1, Asif M Khan, Vladimir Brusic.   

Abstract

Venomous animals produce a myriad of important pharmacological components. The individual components, or venoms (toxins), are used in ion channel and receptor studies, drug discovery, and formulation of insecticides. The toxin data are scattered across public databases which provide sequence and structural descriptions, but very limited functional annotation. The exponential growth of newly identified toxin data has created a need for better data management. Venominformatics is a systematic bioinformatics approach in which classified, consolidated and cleaned venom data are stored into repositories and integrated with advanced bioinformatics tools for the analysis of structure and function of toxins. Venominformatics complements experimental studies and helps reduce the number of essential experiments.

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Year:  2003        PMID: 12715834     DOI: 10.1093/bib/4.1.53

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


  12 in total

1.  CysView: protein classification based on cysteine pairing patterns.

Authors:  Johann Lenffer; Paulo Lai; Wafaa El Mejaber; Asif M Khan; Judice L Y Koh; Paul T J Tan; Seng H Seah; Vladimir Brusic
Journal:  Nucleic Acids Res       Date:  2004-07-01       Impact factor: 16.971

Review 2.  Anticoagulant proteins from snake venoms: structure, function and mechanism.

Authors:  R Manjunatha Kini
Journal:  Biochem J       Date:  2006-08-01       Impact factor: 3.857

3.  Design of bioactive peptides derived from CART sequence isolated from the toadfish Thalassophryne nattereri.

Authors:  Katia Conceição; Gabrielle L de Cena; Verônica A da Silva; Xisto Antonio de Oliveira Neto; Vitor Martins de Andrade; Dayane Batista Tada; Michael Richardson; Sonia A de Andrade; Susana A Dias; Miguel A R B Castanho; Mônica Lopes-Ferreira
Journal:  3 Biotech       Date:  2020-03-06       Impact factor: 2.406

4.  A predictor for toxin-like proteins exposes cell modulator candidates within viral genomes.

Authors:  Guy Naamati; Manor Askenazi; Michal Linial
Journal:  Bioinformatics       Date:  2010-09-15       Impact factor: 6.937

Review 5.  Advances in venomics: Modern separation techniques and mass spectrometry.

Authors:  Tarek Mohamed Abd El-Aziz; Antonio G Soares; James D Stockand
Journal:  J Chromatogr B Analyt Technol Biomed Life Sci       Date:  2020-09-17       Impact factor: 3.205

6.  Bioinformatics and multiepitope DNA immunization to design rational snake antivenom.

Authors:  Simon C Wagstaff; Gavin D Laing; R David G Theakston; Christina Papaspyridis; Robert A Harrison
Journal:  PLoS Med       Date:  2006-06       Impact factor: 11.069

Review 7.  Bioinformatics-Aided Venomics.

Authors:  Quentin Kaas; David J Craik
Journal:  Toxins (Basel)       Date:  2015-06-11       Impact factor: 4.546

8.  Prediction of Toxin Genes from Chinese Yellow Catfish Based on Transcriptomic and Proteomic Sequencing.

Authors:  Bing Xie; Xiaofeng Li; Zhilong Lin; Zhiqiang Ruan; Min Wang; Jie Liu; Ting Tong; Jia Li; Yu Huang; Bo Wen; Ying Sun; Qiong Shi
Journal:  Int J Mol Sci       Date:  2016-04-13       Impact factor: 5.923

9.  ClanTox: a classifier of short animal toxins.

Authors:  Guy Naamati; Manor Askenazi; Michal Linial
Journal:  Nucleic Acids Res       Date:  2009-05-08       Impact factor: 16.971

10.  A comparative in silico characterization of functional and physicochemical properties of 3FTx (three finger toxin) proteins from four venomous snakes.

Authors:  Zahida Yesmin Roly; Md Mahmudul Islam; Md Abu Reza
Journal:  Bioinformation       Date:  2014-05-20
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