Literature DB >> 25385275

VariSNP, a benchmark database for variations from dbSNP.

Gerard C P Schaafsma1, Mauno Vihinen.   

Abstract

For development and evaluation of methods for predicting the effects of variations, benchmark datasets are needed. Some previously developed datasets are available for this purpose, but newer and larger benchmark sets for benign variants have largely been missing. VariSNP datasets are selected from dbSNP. These subsets were filtered against disease-related variants in the ClinVar, UniProtKB/Swiss-Prot, and PhenCode databases, to identify neutral or nonpathogenic cases. All variant descriptions include mapping to reference sequences on chromosomal, genomic, coding DNA, and protein levels. The datasets will be updated with automated scripts on a regular basis and are freely available at http://structure.bmc.lu.se/VariSNP.
© 2014 WILEY PERIODICALS, INC.

Keywords:  benchmark; dbSNP; genetic variation; mutation; variant effect analysis; variant effect prediction; variant position mapping

Mesh:

Year:  2015        PMID: 25385275     DOI: 10.1002/humu.22727

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  22 in total

1.  Types and effects of protein variations.

Authors:  Mauno Vihinen
Journal:  Hum Genet       Date:  2015-01-24       Impact factor: 4.132

2.  ClinPred: Prediction Tool to Identify Disease-Relevant Nonsynonymous Single-Nucleotide Variants.

Authors:  Najmeh Alirezaie; Kristin D Kernohan; Taila Hartley; Jacek Majewski; Toby Dylan Hocking
Journal:  Am J Hum Genet       Date:  2018-09-13       Impact factor: 11.025

3.  Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning.

Authors:  Arun Prasad Pandurangan; Tom L Blundell
Journal:  Protein Sci       Date:  2019-11-25       Impact factor: 6.725

4.  VIPdb, a genetic Variant Impact Predictor Database.

Authors:  Zhiqiang Hu; Changhua Yu; Mabel Furutsuki; Gaia Andreoletti; Melissa Ly; Roger Hoskins; Aashish N Adhikari; Steven E Brenner
Journal:  Hum Mutat       Date:  2019-08-17       Impact factor: 4.878

5.  PON-P and PON-P2 predictor performance in CAGI challenges: Lessons learned.

Authors:  Abhishek Niroula; Mauno Vihinen
Journal:  Hum Mutat       Date:  2017-05-02       Impact factor: 4.878

6.  Investigating the linkage between disease-causing amino acid variants and their effect on protein stability and binding.

Authors:  Yunhui Peng; Emil Alexov
Journal:  Proteins       Date:  2016-01-11

7.  PPVED: A machine learning tool for predicting the effect of single amino acid substitution on protein function in plants.

Authors:  Xiangjian Gou; Xuanjun Feng; Haoran Shi; Tingting Guo; Rongqian Xie; Yaxi Liu; Qi Wang; Hongxiang Li; Banglie Yang; Lixue Chen; Yanli Lu
Journal:  Plant Biotechnol J       Date:  2022-04-27       Impact factor: 13.263

8.  Variant pathogenic prediction by locus variability: the importance of the current picture of evolution.

Authors:  José Luis Cabrera-Alarcon; Jorge García Martinez; José Antonio Enríquez; Fátima Sánchez-Cabo
Journal:  Eur J Hum Genet       Date:  2022-01-26       Impact factor: 5.351

9.  ENTPRISE: An Algorithm for Predicting Human Disease-Associated Amino Acid Substitutions from Sequence Entropy and Predicted Protein Structures.

Authors:  Hongyi Zhou; Mu Gao; Jeffrey Skolnick
Journal:  PLoS One       Date:  2016-03-16       Impact factor: 3.240

10.  PredictSNP2: A Unified Platform for Accurately Evaluating SNP Effects by Exploiting the Different Characteristics of Variants in Distinct Genomic Regions.

Authors:  Jaroslav Bendl; Miloš Musil; Jan Štourač; Jaroslav Zendulka; Jiří Damborský; Jan Brezovský
Journal:  PLoS Comput Biol       Date:  2016-05-25       Impact factor: 4.475

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