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BIODICA: a computational environment for Independent Component Analysis of omics data.
Captier, Nicolas; Merlevede, Jane; Molkenov, Askhat; Seisenova, Ainur; Zhubanchaliyev, Altynbek; Nazarov, Petr V; Barillot, Emmanuel; Kairov, Ulykbek; Zinovyev, Andrei.
Affiliation
  • Captier N; Institut National de la Santé et de la Recherche Médicale (INSERM), U900, F-75005 Paris, France.
  • Merlevede J; Institut Curie, PSL Research University, F-75005 Paris, France.
  • Molkenov A; MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, F-75006 Paris, France.
  • Seisenova A; Laboratoire d'Imagerie Translationnelle en Oncologie, Institut Curie, INSERM U1288, PSL Research University, 91400 Orsay, France.
  • Zhubanchaliyev A; Institut National de la Santé et de la Recherche Médicale (INSERM), U900, F-75005 Paris, France.
  • Nazarov PV; Institut Curie, PSL Research University, F-75005 Paris, France.
  • Barillot E; MINES ParisTech, PSL Research University, CBIO-Centre for Computational Biology, F-75006 Paris, France.
  • Kairov U; National Laboratory Astana, Center for Life Sciences, Nazarbayev University, Nur-Sultan 010000, Kazakhstan.
  • Zinovyev A; National Laboratory Astana, Center for Life Sciences, Nazarbayev University, Nur-Sultan 010000, Kazakhstan.
Bioinformatics ; 38(10): 2963-2964, 2022 05 13.
Article in En | MEDLINE | ID: mdl-35561190
SUMMARY: We developed BIODICA, an integrated computational environment for application of independent component analysis (ICA) to bulk and single-cell molecular profiles, interpretation of the results in terms of biological functions and correlation with metadata. The computational core is the novel Python package stabilized-ica which provides interface to several ICA algorithms, a stabilization procedure, meta-analysis and component interpretation tools. BIODICA is equipped with a user-friendly graphical user interface, allowing non-experienced users to perform the ICA-based omics data analysis. The results are provided in interactive ways, thus facilitating communication with biology experts. AVAILABILITY AND IMPLEMENTATION: BIODICA is implemented in Java, Python and JavaScript. The source code is freely available on GitHub under the MIT and the GNU LGPL licenses. BIODICA is supported on all major operating systems. URL: https://sysbio-curie.github.io/biodica-environment/.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Systematic_reviews Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: France Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Algorithms / Software Type of study: Systematic_reviews Language: En Journal: Bioinformatics Journal subject: INFORMATICA MEDICA Year: 2022 Document type: Article Affiliation country: France Country of publication: United kingdom