Cancer Bioinformatics
Autor Ying Xu, Juan Cui, David Puetten Limba Engleză Hardback – sep 2014
Preț: 388.79 lei
Puncte Express: 583
Carte tipărită la comandă
Livrare economică 13-27 iulie
Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 400.00 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
Specificații
ISBN-13: 9781493913800
ISBN-10: 1493913808
Pagini: 396
Ilustrații: XXVI, 368 p. 68 illus.
Dimensiuni: 160 x 241 x 27 mm
Greutate: 0.76 kg
Ediția:2014
Editura: Springer
Locul publicării:New York, NY, United States
ISBN-10: 1493913808
Pagini: 396
Ilustrații: XXVI, 368 p. 68 illus.
Dimensiuni: 160 x 241 x 27 mm
Greutate: 0.76 kg
Ediția:2014
Editura: Springer
Locul publicării:New York, NY, United States
Public țintă
ResearchCuprins
Basic cancer biology.- Omic data, information derivable and computational needs.- Cancer classification and molecular signature identification.- Understanding cancer at the genomic level.- Elucidation of cancer divers through comparative omic analyses.- Hyaluronic acid: A key facilitator of cancer evolution.- Multiple routes for survival: Understanding how cancer evades apoptosis.- Cancer development in competitive and hostile environments.- Cell proliferation from regulated to deregulated state via epigenomic responses.- Understanding cancer invasion and metastasis.- Cancer after metastasis: The second transformation.- Searching for cancer biomarkers in human body fluids.- In silico investigation of cancer using publicly available data.- Understanding cancer as an evolving complex system: our perspective.
Caracteristici
Focuses on the understanding of cancer biology from an informatics perspective Provides a unified conceptual framework for studying a variety of cancer related problems by considering cancer a process of cell survival through cell proliferation Teaches hypothesis-driven omic data mining and statistical inference of mechanistic relationships important to cancer initiation, progression, metastasis and post-metastasis development Gives a large collection of examples related to different aspects of cancer study using omic data analyses to answer a wide range of questions Includes supplementary material: sn.pub/extras