EGFRIndb – Epidermal Growth Factor Receptor Inhibitor Database

EGFRIndb

:: DESCRIPTION

EGFRIndb is a literature curated database of 4581 small molecule inhibitors that have shown activity against either epidermal growth factor receptor isoforms (EGFR, ErbB2, ErbB4) or mutants of EGFR-TK domain (L858R, T790M, double mutant).

::DEVELOPER

EGFRIndb team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

EGFRIndb: epidermal growth factor receptor inhibitor database.
Yadav IS, Singh H, Khan MI, Chaudhury A, Raghava GP, Agarwal SM.
Anticancer Agents Med Chem. 2014;14(7):928-35.

PRRDB 2.0 – Pattern Recognition Receptor Database

PRRDB 2.0

:: DESCRIPTION

PRRDB is a comprehensive database of pattern recognition receptors and their ligands. This is an updated version of the database PRRDB. It contains extensive information about 467 unique pattern-recognition receptors and 827 ligands manually extracted from ~600 research articles.

::DEVELOPER

PRRDB team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation

PRRDB 2.0: a comprehensive database of pattern-recognition receptors and their ligands.
Kaur D, Patiyal S, Sharma N, Usmani SS, Raghava GPS.
Database (Oxford). 2019 Jan 1;2019. pii: baz076. doi: 10.1093/database/baz076.

tcR 2.2.4 – T Cell Receptor Repertoire Advanced data analysis

tcR 2.2.4

:: DESCRIPTION

tcR is a platform designed for TCR repertoire data analysis in R after preprocessing data with CDR3 extraction and gene alignment software tools such as MiTCR, ImmunoSEQ and MiGEC.

::DEVELOPER

Laboratory of Comparative and Functional Genomic

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows
  • R

:: DOWNLOAD

 tcR

:: MORE INFORMATION

Citation:

tcR: an R package for T cell receptor repertoire advanced data analysis.
Nazarov VI, Pogorelyy MV, Komech EA, Zvyagin IV, Bolotin DA, Shugay M, Chudakov DM, Lebedev YB, Mamedov IZ.
BMC Bioinformatics. 2015 May 28;16:175. doi: 10.1186/s12859-015-0613-1.

MiXCR 3.0.11 – Analysis of T- and B- cell Receptor Repertoire Sequencing data

MiXCR 3.0.11

:: DESCRIPTION

MiXCR is an universal software for fast and accurate analysis of T- and B- cell receptor repertoire sequencing data

::DEVELOPER

MiLaboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / MacOsX
  • JRE
:: DOWNLOAD

 MiXCR

:: MORE INFORMATION

Citation:

Nat Methods. 2015 May;12(5):380-1. doi: 10.1038/nmeth.3364.
MiXCR: software for comprehensive adaptive immunity profiling.
Bolotin DA, Poslavsky S, Mitrophanov I, Shugay M3, Mamedov IZ, Putintseva EV, Chudakov DM.

ARResT / AssignSubsets 20160305 – Robust Subclassification of Chronic Lymphocytic Leukemia based on B cell Receptor IG stereotypy

ARResT / AssignSubsets 20160305

:: DESCRIPTION

ARResT is designed to enable a deep understanding of antigen receptor sequences with a cascade of algorithms and databases.

ARResT/AssignSubsets was built to robustly assign user-submitted sequences as new members to existing subsets of stereotyped antigen receptor sequences, currently applicable to the 19 major subsets of stereotyped B-cell receptors in chronic lymphocytic leukemia (CLL), through sets of rules captured in a statistical model.

::DEVELOPER

The Bioinformatics Analysis Team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

  NO

:: MORE INFORMATION

Citation:

ARResT/AssignSubsets: a novel application for robust subclassification of chronic lymphocytic leukemia based on B cell receptor IG stereotypy.
Bystry V, Agathangelidis A, Bikos V, Sutton LA, Baliakas P, Hadzidimitriou A, Stamatopoulos K, Darzentas N.
Bioinformatics. 2015 Aug 6. pii: btv456.

ANARCI – Antigen Receptor Numbering And Receptor ClassificatIon

ANARCI

:: DESCRIPTION

ANARCI is a tool for numbering amino-acid sequences of antibody and T-cell receptor variable domains.

::DEVELOPER

Oxford Protein Informatics Group (OPIG)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • Python

:: DOWNLOAD

 ANARCI

:: MORE INFORMATION

Citation:

ANARCI: Antigen receptor numbering and receptor classification.
Dunbar J, Deane CM.
Bioinformatics. 2015 Sep 30. pii: btv552.

LYRA 1.0 – Lymphocyte Receptor Automated Modelling

LYRA 1.0

:: DESCRIPTION

The LYRA server predicts structures for either T-Cell Receptors (TCR) or B-Cell Receptors (BCR) using homology modelling.

::DEVELOPER

Center for Biological Sequence Analysis, Technical University of Denmark

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

LYRA, a webserver for lymphocyte receptor structural modeling.
Klausen MS, Anderson MV, Jespersen MC, Nielsen M, Marcatili P.
Nucleic Acids Res. 2015 May 24. pii: gkv535

NRfamPred – Webserver for Nuclear Receptor Proteins and their Sub-family Prediction

NRfamPred

:: DESCRIPTION

NRfamPred is a SVM based two level predictor of nuclear receptor proteins and their sub-family.

::DEVELOPER

NRfamPred team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 NRfamPred

:: MORE INFORMATION

Citation

Sci Rep. 2014 Oct 29;4:6810. doi: 10.1038/srep06810.
NRfamPred: a proteome-scale two level method for prediction of nuclear receptor proteins and their sub-families.
Kumar R, Kumari B, Srivastava A, Kumar M

CCOMP 3.70 – Compare Ligand/Receptor Complexes

CCOMP 3.70

:: DESCRIPTION

CCOMP (Complex COMParison) is a simple command-line tool for comparing ligand/receptor complexes. It can also be used for calculating pairwise all-atom RMSD of slightly different protein structures, taking care of missing atoms, sequence inconsistencies, etc. CCOMP reads two files in PDB format, including both a receptor and a ligand, computes a pairwise sequence alignment of the receptor molecules, generates alpha-carbon superposition of the receptor structures according to the generated alignment, and computes individual deviations per residuum.

::DEVELOPER

Piotr Rotkiewicz

:: SCREENSHOTS

Command Line

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

CCOMP

:: MORE INFORMATION

Citation

W. Sicinska, P. Rotkiewicz,
Computational analysis of the active sites in binary and ternary complexes of the vitamin D receptor,”
J. Ster. Biochem. Mol. Biol., 103 (3-5), 305-309 (2007)