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- GitHub Pages - Jaimes website
A brief interview about my time as researcher at NCMBM, a summary of my scientific career (until 2022), and my transition from academia to industry Although I am back to the public sector since May 2025, so I can give you my opinion in the other direction
- JaimeACastro-Mondragon
jamondra@uio no | jaimicore github io | jaimicore | jaime-castro-mondragon am a computational biologist with 11 years of experience in research, sequence analysis, methods development and data visualisation I have worked in both the academic and private sector My main expertise is the development of algorithms to analyze multivariate data and apply them in a wider range of biomedical fields
- Combining transcriptional and post-transcriptional regulation to . . .
Hsa-miR-29a-5p We used a third, Independent, breast cancer cohort (Metabric, n = 1282) to draw the survival plots For each mutated sample (columns), we selected the dysregulated target genes (rows) of the highlighted miRNAs The dysregulated miRNA-target genes are enriched in key cancer pathways
- Development of bioinformatics methods for the analysis of large . . .
Development of bioinformatics methods for the analysis of large collections of transcription factor binding motifs: positional motif enrichment and motif clustering Jaime Abraham CASTRO-MONDRAGON 2017-06-28
- Publications with contribution
22 Rauluseviciute I, Launay T, Barzaghi G, Nikumbh S, Lenhard B, Krebs AR, Castro-Mondragon JA, and Mathelier A (2022) Identification of transcription factor co-binding patterns with non-negative matrix factorization Nucleic Acids Research i My contributions to this study were the conceptualization of the project and mplementation of some analysis O F 21 Rauluseviciute I*, Riudavets-Puig R
- École Normale Supérieu - GitHub Pages
ABSTRACT Transcription factors binding motifs (TFBM) are classically represented either as consensus strings (IUPAC, regular expressions), or as position-specific scoring matrices (PSSM) Thousands of curated TFBM are available in specialized databases (JASPAR, RegulonDB, TRANSFAC, etc), built from collections of transcription factor binding sites (TFBS) obtained from various experimental
- JASPAR 2022 motif discovery pipeline and motif annotation
Summary JASPAR(1) is an open-access database of curated, non-redundant transcription factor (TF)-binding profiles stored as position frequency matrices (PFMs) for TFs across multiple species in six taxonomic groups: Vertebrates, Plants, Fungi, Insects and Urochordata
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