Discovering Differentially Expressed Genes in Yeast Stress Data

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Antonio Goncalves (Autor) Outra; Irene Ong (Autor) Outra; Jeffrey A Lewis (Autor) Outra; Vitor Santos Costa (Autor) FCUP

Ata de Conferência Internacional

Título: 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS)

Páginas: 537-538

27th IEEE International Symposium on Computer-Based Medical Systems (CBMS)

New York, NY, MAY 27-29, 2014

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Biotecnologia ambiental

Outras Informações

ID Authenticus: P-009-VHP

DOI: 10.1109/cbms.2014.127

Abstract (EN): Transcriptional regulation plays an important role in every cellular decision. Gaining an understanding of the dynamics that govern how a cell will respond to diverse environmental cues is difficult using intuition alone. We try to discover how genes interact when submitted to stress by exploring techniques of gene expression data analysis. We use several types of data, including high-throughput data. These results will help us recreate plausible regulatory networks by using a probabilistic logical model. Hence, network hypotheses can be generated from existing gene expression data for use by experimental biologists.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 2