Analysis of time-course gene expression profiles to study regulation of cell growth in fed-batch bioreactors

Lin, Yanzhu; Lehmann, Kim; Brohawn, Philip Z.; Liu, Zheng; Agarwal, Nitin

doi:10.1016/j.bej.2015.06.014

Search citation statements

Order By: Relevance

Paper Sections

Select...

Fig 2 Exemp1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2015

Publication Types

Select...

Other1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 43 publications

(80 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [11], scientists use sparse partial least squares analysis as a procedure for multiclass classification in order to identify specific genes of interest from a large number of genes, selecting only those genes highly correlated to the phenotype and discarding the non-relevant ones.…”

Section: Fig 2 Exempmentioning

confidence: 99%

An integrated gene expression analysis approach

Petre

Buiu

2015

2015 E-Health and Bioengineering Conference (EHB)

View full text Add to dashboard Cite

Big data is one of the hottest topics in information science. It has become the key for biological and medical discovery and research, making developing new methods for data management, analysis and accessibility a great challenge in the field. This study proposes an integrated gene analysis approach, in terms of classification and prediction methods for understanding, analyzing and interpretation of biological data related to cancer. The final aim of this study is to predict and classify several subtypes of cancer, based on gene expression.

show abstract

Section: Fig 2 Exempmentioning

confidence: 99%