1.

Record Nr.

UNINA9910162857403321

Autore

Moses Alan

Titolo

Statistical modeling and machine learning for molecular biology / / Alan Moses, University of Toronto, Canada

Pubbl/distr/stampa

Boca Raton : , : CRC Press, , [2017]

©2017

ISBN

1-4822-5862-5

1-315-37226-6

1-4822-5860-9

Descrizione fisica

1 online resource

Collana

Chapman & Hall/CRC mathematical and computational biology series

Disciplina

572.8

Soggetti

Molecular biology - Statistical methods

Molecular biology - Data processing

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

section 1. Overview -- section 2. Clustering -- section 3. Regression -- section 4. Classification.

Sommario/riassunto

Molecular biologists are performing increasingly large and complicated experiments, but often have little background in data analysis. The book is devoted to teaching the statistical and computational techniques molecular biologists need to analyze their data. It explains the big-picture concepts in data analysis using a wide variety of real-world molecular biological examples such as eQTLs, ortholog identification, motif finding, inference of population structure, protein fold prediction and many more. The book takes a pragmatic approach, focusing on techniques that are based on elegant mathematics yet are the simplest to explain to scientists with little background in computers and statistics.