ChemmineR: a compound mining framework for R

By Yiqun Cao, A. Charisi, Li-Chang Cheng, Tao Jiang, Thomas Girke. Bioinform., 2008

338 citations recorded by the source corpus.

Motivation: Software applications for structural similarity searching and clustering of small molecules play an important role in drug discovery and chemical genomics. Here, we present the first open-source compound mining framework for the popularstatistical programming environment R. The integration with a powerful statistical environment maximizes the flexibility, expandability and programmability of the provided analysis functions. Results: We discuss the algorithms and compound mining utilities provided by the R package ChemmineR. It contains functions for structural similarity searching, clustering of compound libraries with a wide spectrum of classification algorithms and various utilities for managing complex compound data. It also offers a wide range of visualization functions for compound clusters and chemical structures. The package is well integrated with the online ChemMine environment and allows bidirectional communications between the two services. Availability: ChemmineR is freely available as an R package from the ChemMine project site: http://bioweb.ucr.edu/ChemMineV2/chemminer Contact: thomas.girke@ucr.edu

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b00b3e7ff2e27ee6ca556674f47544c9afe41499

How researchers see this paper

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In Computational Theory and Mathematics

1. João P. G. L. M. Rodrigues
2. Alexandre M. J. J. Bonvin
3. Li C. Xue
4. Anna Vangone
5. Adrien S. J. Melquiond
6. Mikael E. Trellet
7. Panagiotis I. Koukos
8. Jorge Roel‐Touris

In Materials Chemistry

1. João P. G. L. M. Rodrigues
2. Zeynep Kurkcuoglu
3. Alexandre M. J. J. Bonvin
4. Adrien S. J. Melquiond
5. Mikael E. Trellet
6. Panagiotis I. Koukos
7. Jorge Roel‐Touris
8. Cunliang Geng

In Molecular Biology

1. Alexandre M. J. J. Bonvin
2. João P. G. L. M. Rodrigues
3. Zeynep Kurkcuoglu
4. Panagiotis I. Koukos
5. Li C. Xue
6. Jorge Roel‐Touris
7. Adrien S. J. Melquiond
8. Mikael E. Trellet

Citations in the corpus

• Performance of HADDOCK and a simple contact-based protein–ligand binding affinity predictor in the D3R Grand Challenge 2 (2017, methodology): “We calculated the ligand similarity using Atom Pair (AP) and Maximum Common Substructure (MCS) measurements, as implemented in ChemmineR and fmcsR packages [31, 32].”