Form of presentation | Articles in Russian journals and collections |
Year of publication | 2013 |
|
Valente Andre Khaver , author
Rizvanov Albert Anatolevich, author
Khaybullina Svetlana Francevna, author
|
Other authors |
P.J. Oliveira; A.Palotás |
Bibliographic description in the original language |
Valente A.X.C.N. Biological Insight, High-Throughput Datasets and the Nature of Neuro-Degenerative Disorders / A.X.C.N. Valente, P.J. Oliveira, S.F. Khaiboullina, A. Palotás, A.A. Rizvanov // Current Drug Metabolism. – 2013. – Vol.14. – P.814-818. |
Annotation |
Life sciences are experiencing a historical shift towards a quantitative, data-rich regime. This transition has been associated with the advent of bio-informatics: mathematicians, physicists, computer scientists and statisticians are now commonplace in the field, working on the analysis of ever larger data-sets. An open question regarding what should drive scientific progress in this new era remains: will biological insight become increasingly irrelevant in a world of hypothesis-free, unbiased data analysis? This piece offers a different perspective, pin-pointing that biological thought is more-than-ever relevant in a data-rich setting. Some of the novel highthroughput information being acquired in the field of neuro-degenerative disorders is highlighted here. As but one example of how theory and experiment can interact in this new reality, our efforts in developing an idiopathic neuro-degenerative disease hematopoietic stemcell ageing theory are described. |
Keywords |
Bio-informatics, biological insight, high-throughput data, data analysis, neuro-degenerative disease |
The name of the journal |
CURR DRUG METAB
|
URL |
http://www.ncbi.nlm.nih.gov/pubmed/23937175 |
Please use this ID to quote from or refer to the card |
https://repository.kpfu.ru/eng/?p_id=93708&p_lang=2 |
Full metadata record |
Field DC |
Value |
Language |
dc.contributor.author |
Valente Andre Khaver |
ru_RU |
dc.contributor.author |
Rizvanov Albert Anatolevich |
ru_RU |
dc.contributor.author |
Khaybullina Svetlana Francevna |
ru_RU |
dc.date.accessioned |
2013-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2013-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2013 |
ru_RU |
dc.identifier.citation |
Valente A.X.C.N. Biological Insight, High-Throughput Datasets and the Nature of Neuro-Degenerative Disorders / A.X.C.N. Valente, P.J. Oliveira, S.F. Khaiboullina, A. Palotás, A.A. Rizvanov // Current Drug Metabolism. – 2013. – Vol.14. – P.814-818. |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/eng/?p_id=93708&p_lang=2 |
ru_RU |
dc.description.abstract |
CURR DRUG METAB |
ru_RU |
dc.description.abstract |
Life sciences are experiencing a historical shift towards a quantitative, data-rich regime. This transition has been associated with the advent of bio-informatics: mathematicians, physicists, computer scientists and statisticians are now commonplace in the field, working on the analysis of ever larger data-sets. An open question regarding what should drive scientific progress in this new era remains: will biological insight become increasingly irrelevant in a world of hypothesis-free, unbiased data analysis? This piece offers a different perspective, pin-pointing that biological thought is more-than-ever relevant in a data-rich setting. Some of the novel highthroughput information being acquired in the field of neuro-degenerative disorders is highlighted here. As but one example of how theory and experiment can interact in this new reality, our efforts in developing an idiopathic neuro-degenerative disease hematopoietic stemcell ageing theory are described. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
Bio-informatics |
ru_RU |
dc.subject |
biological insight |
ru_RU |
dc.subject |
high-throughput data |
ru_RU |
dc.subject |
data analysis |
ru_RU |
dc.subject |
neuro-degenerative disease |
ru_RU |
dc.title |
Biological Insight, High-Throughput Datasets and the Nature of Neuro-Degenerative Disorders |
ru_RU |
dc.type |
Articles in Russian journals and collections |
ru_RU |
|