Tag: Change

CSM-AB / mCSM-AB / mCSM-AB2 / mmCSM-AB- Predicting Antibody-antigen Binding Affinity

CSM-AB / mCSM-AB / mCSM-AB2 / mmCSM-AB

:: DESCRIPTION

CSM-AB is a machine learning method capable of predicting antibody-antigen binding affinity by modelling interaction interfaces as graph-based signatures.

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

mCSM-AB2 is an updated and refined version approach, capable of accurately modelling the effects of mutations on antibody-antigen binding affinity, through the inclusion of evolutionary and energetic terms.

mmCSM-AB is a tool for analysing the effects of introducing multiple point mutations on antibody-antigen binding affinity.

::DEVELOPER

Biosig Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Myung Y, Pires DEV, Ascher DB.
CSM-AB: graph-based antibody-antigen binding affinity prediction and docking scoring function.
Bioinformatics. 2021 Nov 4:btab762. doi: 10.1093/bioinformatics/btab762. Epub ahead of print. PMID: 34734992.

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 May 23. pii: gkw458.

Myung Y, Rodrigues CHM, Ascher DB, Pires DEV.
mCSM-AB2: guiding rational antibody design using graph-based signatures.
Bioinformatics. 2020 Mar 1;36(5):1453-1459. doi: 10.1093/bioinformatics/btz779. PMID: 31665262.

Myung Y, Pires DEV, Ascher DB.
mmCSM-AB: guiding rational antibody engineering through multiple point mutations.
Nucleic Acids Res. 2020 Jul 2;48(W1):W125-W131. doi: 10.1093/nar/gkaa389. PMID: 32432715; PMCID: PMC7319589.

CMDS 1.0 – Identify Recurrent DNA Copy Number Changes

CMDS 1.0

:: DESCRIPTION

CMDS (Correlation Matrix Diagonal Segmentation ) is a R & C programs for DNA copy number analysis: current copy number aberration indentification in multiple samples (with no need of single-sample calling). Developed for a quick analysis of high resolution and large population data.

::DEVELOPER

Qunyuan Zhang  (qunyuan@wustl.edu)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  CMDS

:: MORE INFORMATION

Citation:

CMDS: a population-based method for identifying recurrent DNA copy number aberrations in cancer from high-resolution data
Qunyuan Zhang, Li Ding, David E. Larson, Daniel C. Koboldt, Michael D. McLellan, Ken Chen, Xiaoqi Shi, Aldi Kraja, Elaine R. Mardis, Richard K. Wilson, Ingrid B. Boreki and Michael A. Province
Bioinformatics (2009)doi: 10.1093/bioinformatics/btp

LFC 1.0 – Count Ratio Model Fold Changes

LFC 1.0

:: DESCRIPTION

LFC is a fundamentally different approach by directly modeling count ratios and reveal that bias also affects fold changes severely.

::DEVELOPER

Institut für Informatik, Ludwig-Maximilians-Universität München

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Java

:: DOWNLOAD

 LFC

:: MORE INFORMATION

Citation

Count ratio model reveals bias affecting NGS fold changes.
Erhard F, Zimmer R.
Nucleic Acids Res. 2015 Jul 8. pii: gkv696.

iStable – Integrated Predictor for Protein Stability change upon Single Mutation

iStable

:: DESCRIPTION

iStable ,an integrated predictor, constructed by using sequence information and prediction results from different element predictors.

::DEVELOPER

Natural Computing and Bioinformatics Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2013;14 Suppl 2:S5. doi: 10.1186/1471-2105-14-S2-S5. Epub 2013 Jan 21.
iStable: off-the-shelf predictor integration for predicting protein stability changes.
Chen CW, Lin J, Chu YW.

chromEvol 2.0 – Analyze Changes in Chromosome-number along a Phylogeny

chromEvol 2.0

:: DESCRIPTION

 chromEvol is a program for analyzing changes in chromosome-number along a phylogeny and for the inference of polyploidy.

::DEVELOPER

Mayrose Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux

:: DOWNLOAD

   chromEvol

:: MORE INFORMATION

Citation

Mayrose I, Barker MS, Otto SP. 2010.
Probabilistic models of chromosome number evolution and the inference of polyploidy.
Systematic Biology. 59(2):132-144

BeAtMuSiC 1.0 – Prediction of Binding Affinity Changes upon Mutations

BeAtMuSiC 1.0

:: DESCRIPTION

The BeAtMuSiC program evaluates the change in binding affinity between proteins (or protein chains) caused by single-site mutations in their sequence.

::DEVELOPER

Service de Biomodélisation, Bioinformatique et Bioprocédés (3BIO)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2013 Jul;41(Web Server issue):W333-9. doi: 10.1093/nar/gkt450. Epub 2013 May 30.
BeAtMuSiC: Prediction of changes in protein-protein binding affinity on mutations.
Dehouck Y, Kwasigroch JM, Rooman M, Gilis D.

CNAnova 1.0 – Identify Recurrent Regions of Copy Number Changes

CNAnova 1.0

:: DESCRIPTION

CNAnova is a stand-alone software package for identifying recurrent regions of copy number aberrations (CNAs) using SNP microarray data. It runs from the command line on the Linux platforms and is composed of several modules written in the R programming language.

::DEVELOPER

Sergii Ivakhno

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

  CNAnova

:: MORE INFORMATION

Citation:

Bioinformatics. 2010 Jun 1;26(11):1395-402. Epub 2010 Apr 18.
CNAnova: a new approach for finding recurrent copy number abnormalities in cancer SNP microarray data.
Ivakhno S, Tavaré S.

MUpro 1.1 – Prediction of Protein Stability Changes for Single Site Mutations from Sequences

MUpro 1.1

:: DESCRIPTION

MUpro is a set of machine learning programs to predict how single-site amino acid mutation affects protein stability. We developed two machine learning methods: Support Vector Machines and Neural Networks. Both of them were trained on a large mutation dataset and show accuracy above 84% via 20 fold cross validation, which is better than other methods in the literature. One advantage of our methods is that they do not require tertiary structures to predict protein stability changes. Our experimental results show that the prediction accuracy using sequence information alone is comparable to that of using tertiary structures. So even you do not have protein tertiary structures available, you still can use this server to get rather accurate prediction. Of course, if you provide tertiary structures, our methods will take advantage of them and you might get slightly better predictions.

::DEVELOPER

Institute for Genomics and Bioinformatics

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MUpro

:: MORE INFORMATION

Citation:

J. Cheng, A. Randall, and P. Baldi.
Prediction of Protein Stability Changes for Single Site Mutations Using Support Vector Machines.
Proteins. 2006 Mar 1;62(4):1125-32.