š° Welcome to MyBunny.TV ā Your Gateway to Unlimited Entertainment! š°
Enjoy 10,000+ Premium HD Channels, thousands of movies & series, and experience lightning-fast instant activation.
Reliable, stable, and built for the ultimate streaming experience ā no hassles, just entertainment! MyBunny.TV ā Cheaper Than Cable ⢠Up to 35% Off Yearly Plans ⢠All NFL, ESPN, PPV Events Included š°
š Join the fastest growing IPTV community today and discover why everyone is switching to MyBunny.TV!
Umer S. Computational Techniques for Biological Sequence Analysis 2025
To start this P2P download, you have to install a BitTorrent client like
qBittorrent
Category:Other Total size: 21.47 MB Added: 2 months ago (2025-06-23 11:52:01)
Share ratio:14 seeders, 0 leechers Info Hash:63454820172CEF10674D7616C17335A34FBDFCAC Last updated: 4 hours ago (2025-09-19 00:43:42)
Report Bad Torrent
×
Description:
Textbook in PDF format
This book provides an overview of basic and advanced computational techniques for analyzing and understanding protein, RNA, and DNA sequences. It covers effective computing techniques for DNA and protein classifications, evolutionary and sequence information analysis, evolutionary algorithms, and ensemble algorithms. Furthermore, the book reviews the role of machine learning techniques, artificial intelligence, ensemble learning, and sequence-based features in predicting post-translational modifications in proteins, DNA methylation, and mRNA methylation, along with their functional implications. The book also discusses the prediction of proteināprotein and proteināDNA interactions, protein structure, and function using computational methods. It also presents techniques for quantitative analysis of proteināDNA interactions and protein methylation and their involvement in gene regulation. Additionally, the use of nature-inspired algorithms to gain insights into gene regulatory mechanisms and metabolic pathways in human diseases is explored. This book acts as a useful reference for bioinformaticians and computational biologists working in the fields of molecular biology, genomics, and bioinformatics