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This book is a lab manual which can be integrated with bioinformatics course. The field of bioinformatics is advancing at a remarkable rate. With the development of new analytical techniques that make use of the latest advances in machine learning and data science, today s biologists are gaining fantastic new insights into the natural world s most complex systems. This book includes a lab-based manual that can assist students handling large biological data. It aims to help students and researchers understand (1) the importance of horizontal transfer in the spread of antibiotic resistance, and…mehr

Produktbeschreibung
This book is a lab manual which can be integrated with bioinformatics course. The field of bioinformatics is advancing at a remarkable rate. With the development of new analytical techniques that make use of the latest advances in machine learning and data science, today s biologists are gaining fantastic new insights into the natural world s most complex systems. This book includes a lab-based manual that can assist students handling large biological data. It aims to help students and researchers understand (1) the importance of horizontal transfer in the spread of antibiotic resistance, and in biology more broadly; (2) how protein and nucleic acid sequences are used to determine phylogenetic trees and the genetic relationship between organisms; (3) how sequence comparisons can be used to infer protein function; and (4) how to analyze high-throughput sequencing data to do gene expression analysis. This book is valuable for researchers, teachers and students, as well as any readers who are interested in bioinformatics.
Autorenporträt
Sufang Wang, PhD, graduated from Purdue University in May 2017, majoring in Bioinformatics. She joined Northwestern Polytechnical University as associate professor in June 2017. Her research focuses on the use of next-generation sequencing in genomics and transcriptomics. She is also interested in genome-wide association study in plants. She has published over 20 scientific papers.

Michael Gribskov, received his PhD from the University of Wisconsin-Madison in 1985. After post-doctoral studies at UCLA and research at the NCI Frederick Cancer Research and Development Center, Dr. Gribskov joined the San Diego Supercomputer Center at UC San Diego, where he was also adjunct professor of Biology. From 2003 to 2007, Dr. Gribskov was president of the International Society for Computational Biology, the largest international society for bioinformatics and computational biology. In 2004, he joined Purdue University as professor of Biological Sciences. His interests include the relationship between macromolecular sequences (DNA, RNA, and proteins) and their evolution, structure and function, and biological networks that control and integrate the cellular development and function. In addition, his work includes developing databases and computational tools for functional genomics, and developing systems that federate knowledge across multiple electronic resources. Dr. Gribskov has published over 120 scientific papers with over 25000 total citations.