EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link: https://ebookbell.com/faq

We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.

For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Bioinformatics For Geneticists 1st Edition Michael R Barnes

SKU: BELL-2431122

$ 31.00 ~~$ 45.00~~ (-31%)

0 reviews

Bioinformatics For Geneticists 1st Edition Michael R Barnes instant download after payment.

Publisher: Wiley

File Extension: PDF

File size: 4.41 MB

Pages: 433

Author: Michael R. Barnes, Ian C. Gray

ISBN: 9780470843949, 9780470843932, 0470843942, 0470843934

Language: English

Year: 2003

Edition: 1

Product desciption

Bioinformatics For Geneticists 1st Edition Michael R Barnes by Michael R. Barnes, Ian C. Gray 9780470843949, 9780470843932, 0470843942, 0470843934 instant download after payment.

This timely book illustrates the value of bioinformatics, not simply as a set of tools but rather as a science increasingly essential to navigate and manage the host of information generated by genomics and the availability of completely sequenced genomes. Bioinformatics can be used at all stages of genetics research: to improve study design, to assist in candidate gene identification, to aid data interpretation and management and to shed light on the molecular pathology of disease-causing mutations. Written specifically for geneticists, this book explains the relevance of bioinformatics showing how it may be used to enhance genetic data mining and markedly improve genetic analysis.