New developments in cancer-related computational statistics.

Abstract:

:A brief overview is presented of recently developed and currently emerging statistical and computational techniques that have been proved to be highly helpful in handling the avalanche of the new type of data generated by modern high-throughput technologies in experimental biology. The review, in no way comprehensive, focuses attention on Bayesian Networks, Hidden Markov Chain, and methods of chaotic dynamics for time-course genomic data; innovative methods in optimization and clustering; and multiple testing in the context of identification of differentially expressed genes.

journal_name

Ann N Y Acad Sci

authors

Rosenfeld S

doi

10.1196/annals.1310.004

subject

Has Abstract

pub_date

2004-05-01 00:00:00

pages

22-31

eissn

0077-8923

issn

1749-6632

pii

1020/1/22

journal_volume

1020

pub_type

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