EDBT 2026 Demo / reviewers in the wild / expert
Ainur Seisenova
dblp:321/4095
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0001-7785-8433ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › gene expression analysis
independent component analysis |
0.6 | 1 | 2022 | BIODICA: a computational environment for Independent Component Analysis of omics data · Bioinform. 2022 |
Bioinformatics and computational biology
omics data analysis |
0.6 | 1 | 2022 | BIODICA: a computational environment for Independent Component Analysis of omics data · Bioinform. 2022 |
Methods — techniques the papers use, named apart from their topics
stabilization procedure · 0.6independent component analysis · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | BIODICA: a computational environment for Independent Component Analysis of omics dataabstractSUMMARY: 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/. Nicolas Captier, Jane Merlevede, Askhat Molkenov, Ainur Seisenova, Altynbek Zhubanchaliyev, Petr V. Nazarov, Emmanuel Barillot, Ulykbek Kairov, Andrei Yu. Zinovyev |
Bioinform. | 4 |