Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset


Autoria(s): Bauer, Chris; Kleinjung, Frank; Smith, Celia J.; Towers, Mark W.; Tiss, Ali; Chadt, Alexandra; Dreja, Tanja; Beule, Dieter; Al-Hasani, Hadi; Reinert, Knut; Schuchhardt, Johannes; Cramer, Rainer
Data(s)

09/05/2011

Resumo

Diabetes like many diseases and biological processes is not mono-causal. On the one hand multifactorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.

Formato

text

Identificador

http://centaur.reading.ac.uk/22025/1/1471-2105-12-140.pdf

Bauer, C., Kleinjung, F., Smith, C. J. <http://centaur.reading.ac.uk/view/creators/90003936.html>, Towers, M. W., Tiss, A. <http://centaur.reading.ac.uk/view/creators/90002793.html>, Chadt, A., Dreja, T., Beule, D., Al-Hasani, H., Reinert, K., Schuchhardt, J. and Cramer, R. <http://centaur.reading.ac.uk/view/creators/90000907.html> (2011) Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset. BMC Bioinformatics, 12. 140. ISSN 1471-2105 doi: 10.1186/1471-2105-12-140 <http://dx.doi.org/10.1186/1471-2105-12-140>

Idioma(s)

en

Publicador

BioMed Central

Relação

http://centaur.reading.ac.uk/22025/

creatorInternal Smith, Celia J.

creatorInternal Tiss, Ali

creatorInternal Cramer, Rainer

http://dx.doi.org/10.1186/1471-2105-12-140

10.1186/1471-2105-12-140

Tipo

Article

PeerReviewed