𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Classification of human ovarian tumors using multivariate data analysis of polypeptide expression patterns

✍ Scribed by Alaiya, Ayodele; Franzen, Bo; Hagman, Anders; Linder, Stig; Auer, Gert


Book ID
109830453
Publisher
Nature Publishing Group
Year
2001
Tongue
English
Weight
28 KB
Volume
27
Category
Article
ISSN
1061-4036

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


Classification of human ovarian tumors u
✍ Ayodele A. Alaiya; Bo FranzΓ©n; Anders Hagman; Claes SilfverswΓ€rd; Birgitta Mober πŸ“‚ Article πŸ“… 2000 πŸ› John Wiley and Sons 🌐 French βš– 223 KB πŸ‘ 2 views

Large amounts of data on quantitative gene expression are generated by procedures such as 2-DE analysis of proteins or cDNA microarrays. Quantitative molecular variation may potentially be used for the development of methods for the classification of tumors. We used here the statistical concepts of

Molecular classification of borderline o
✍ Ayodele A. Alaiya; Bo FranzΓ©n; Anders Hagman; Bjarte Dysvik; Uwe J. Roblick; Sus πŸ“‚ Article πŸ“… 2002 πŸ› John Wiley and Sons 🌐 French βš– 488 KB

## Abstract Ovarian tumors range from benign to aggressive malignant tumors, including an intermediate class referred to as borderline carcinoma. The prognosis of the disease is strongly dependent on tumor classification, where patients with borderline tumors have much better prognosis than patient

[Studies in Classification, Data Analysi
✍ Fichet, Bernard; Piccolo, Domenico; Verde, Rosanna; Vichi, Maurizio πŸ“‚ Article πŸ“… 2010 πŸ› Springer Berlin Heidelberg 🌐 German βš– 506 KB

The growing capabilities in generating and collecting data has risen an urgent need of new techniques and tools in order to analyze, classify and summarize statistical information, as well as to discover and characterize trends, and to automatically bag anomalies. This volume provides the latest adv