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Amazon verified reviews

Yannick Pouliot Oct 13, 2015

I've been in computational biology for a long time, and I find this to be one of the most impressive practical and comprehensive books I've come across (and I go through a lot!) It provides an incredibly wide survey of different domains of computational biology (e.g., protein structure, genomics, and much more), combined with lots of good Python programming advice (e.g., use of IPython/Jupyter notebooks, provided by the author). And it's about as up to date as imaginable -- quite a tour de force!

Amazon Verified review

Stefanobia Dec 01, 2016

Non sono in grado di recensire il prodotto in quanto non ho queste conoscenze, libro perfetto senza nessun segno o danneggiamento

AR Nov 10, 2018

En mi caso, con poca experiencia en bioinformática, este libro me ha proporcionado una visión general de como se usa python en este campo.

JoseJaime Jan 13, 2016

Awesome, clear, updated. This is an must be readed textbook for bioinformaticians and biologist that want to tackle bioinformatics with Python.Python basis are mandatory.

Loris Aug 29, 2015

This book is an excellent bioinformatics cookbook and it covers a vast range of topics, ranging from next generation sequencing to population genetics and phylogenetics. However to take fully advantage of the book is highly recommended to have both a medium-high knowledge of python and some experience in bioinformatics. Each chapter provides python code to reproduce the analyses the author performs. Even though the author explains the code in details, the code often is not trivial and a certain experience with python is required. Similarly, a previous knowledge of bioinformatic technologies is desirable as the book often uses a terminology (such as fastq, bam, vcf, etc.) that won’t be familiar to those that haven’t any experience in bioinformatics.The book is well organized and structured. The first chapter helps the reader to set up a python environment through Anaconda or Docker. In the following chapter the author starts to talk about bioinformatics and the first topic he touches is NGS (next generation sequencing). I found this chapter very interesting as it shows how to deal efficiently with the usually huge fastq files and how to perform simple but useful analyses such as quality control of the sequencing reads by position. In the same chapter the author talks about the variant call format (VCF) and how to work with it through libraries such as pyVCF. The next chapter is dedicated to whole genome sequences in fasta format and to genome annotations in GFF/GTF formats. The following chapters are about population genetics and phylogenetics. Even though I’m not an expert of these fields and I was not aware of the formats used (such as genepop) I could enjoy the reading and the code was straightforward enough to be easily understandable. Then the author explains how to use PDB (the protein data bank) and the software PyMol. A very interesting (and in my opinion important) chapter is the last one where the author discusses how to deal efficiently with big genomics datasets. Here the authors talks about concurrency and ipython parallel computing, and shows how it is possible to speed up your python code by using libraries such as Cython and Numba.Overall the book is well written and organized and is a good cookbook for bioinformaticians.

Bioinformatics with Python Cookbook: Learn how to use modern Python bioinformatics libraries and applications to do cutting-edge research in computational biology

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