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Items: 1 to 20 of 98


mCSM: predicting the effects of mutations in proteins using graph-based signatures.

Pires DE, Ascher DB, Blundell TL.

Bioinformatics. 2014 Feb 1;30(3):335-42. doi: 10.1093/bioinformatics/btt691. Epub 2013 Nov 26.


mCSM-NA: predicting the effects of mutations on protein-nucleic acids interactions.

Pires DE, Ascher DB.

Nucleic Acids Res. 2017 Apr 4. doi: 10.1093/nar/gkx236. [Epub ahead of print]


mCSM-AB: a web server for predicting antibody-antigen affinity changes upon mutation with graph-based signatures.

Pires DE, Ascher DB.

Nucleic Acids Res. 2016 Jul 8;44(W1):W469-73. doi: 10.1093/nar/gkw458. Epub 2016 May 23.


INPS: predicting the impact of non-synonymous variations on protein stability from sequence.

Fariselli P, Martelli PL, Savojardo C, Casadio R.

Bioinformatics. 2015 Sep 1;31(17):2816-21. doi: 10.1093/bioinformatics/btv291. Epub 2015 May 7.


DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach.

Pires DE, Ascher DB, Blundell TL.

Nucleic Acids Res. 2014 Jul;42(Web Server issue):W314-9. doi: 10.1093/nar/gku411. Epub 2014 May 14.


Protein stability: a single recorded mutation aids in predicting the effects of other mutations in the same amino acid site.

Wainreb G, Wolf L, Ashkenazy H, Dehouck Y, Ben-Tal N.

Bioinformatics. 2011 Dec 1;27(23):3286-92. doi: 10.1093/bioinformatics/btr576. Epub 2011 Oct 13.


PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality.

Dehouck Y, Kwasigroch JM, Gilis D, Rooman M.

BMC Bioinformatics. 2011 May 13;12:151. doi: 10.1186/1471-2105-12-151.


Effects of p51/p63 missense mutations on transcriptional activities of p53 downstream gene promoters.

Kato S, Shimada A, Osada M, Ikawa S, Obinata M, Nakagawara A, Kanamaru R, Ishioka C.

Cancer Res. 1999 Dec 1;59(23):5908-11.


Cancer missense mutations alter binding properties of proteins and their interaction networks.

Nishi H, Tyagi M, Teng S, Shoemaker BA, Hashimoto K, Alexov E, Wuchty S, Panchenko AR.

PLoS One. 2013 Jun 14;8(6):e66273. doi: 10.1371/journal.pone.0066273. Print 2013.


SDM--a server for predicting effects of mutations on protein stability and malfunction.

Worth CL, Preissner R, Blundell TL.

Nucleic Acids Res. 2011 Jul;39(Web Server issue):W215-22. doi: 10.1093/nar/gkr363. Epub 2011 May 18.


Prediction of protein disorder on amino acid substitutions.

Anoosha P, Sakthivel R, Gromiha MM.

Anal Biochem. 2015 Dec 15;491:18-22. doi: 10.1016/j.ab.2015.08.028. Epub 2015 Sep 6.


BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.

Dehouck Y, Kwasigroch JM, Rooman M, Gilis D.

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W333-9. doi: 10.1093/nar/gkt450. Epub 2013 May 30.


The impact of p53 protein core domain structural alteration on ovarian cancer survival.

Rose SL, Robertson AD, Goodheart MJ, Smith BJ, DeYoung BR, Buller RE.

Clin Cancer Res. 2003 Sep 15;9(11):4139-44.


Disease risk of missense mutations using structural inference from predicted function.

Horst JA, Wang K, Horst OV, Cunningham ML, Samudrala R.

Curr Protein Pept Sci. 2010 Nov;11(7):573-88.


Importance of mutant position in Ramachandran plot for predicting protein stability of surface mutations.

Gromiha MM, Oobatake M, Kono H, Uedaira H, Sarai A.

Biopolymers. 2002 Aug 5;64(4):210-20.


Mutants of the tumour suppressor p53 L1 loop as second-site suppressors for restoring DNA binding to oncogenic p53 mutations: structural and biochemical insights.

Merabet A, Houlleberghs H, Maclagan K, Akanho E, Bui TT, Pagano B, Drake AF, Fraternali F, Nikolova PV.

Biochem J. 2010 Mar 29;427(2):225-36. doi: 10.1042/BJ20091888.


Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods.

Mathe E, Olivier M, Kato S, Ishioka C, Hainaut P, Tavtigian SV.

Nucleic Acids Res. 2006 Mar 6;34(5):1317-25. Print 2006.

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