BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Computational Approaches In Molecular Interaction Analysis: Predicting Protein Complexes, Host-pathogen Interactions, And Protein Function From Interactome Data

Computational Approaches In Molecular Interaction Analysis: Predicting Protein Complexes, Host-pathogen Interactions, And Protein Function From Interactome Data

Computational Approaches In Molecular Interaction Analysis: Predicting Protein
Stock photo: cover may vary

Computational Approaches In Molecular Interaction Analysis: Predicting Protein Complexes, Host-pathogen Interactions, And Protein Function From Interactome Data Hardback - 2025

by Limsoon Wong (Editor)

Add to wish list
  • Used
  • very good
  • Hardback
Used - Very good

Description

WSPC, 2/25/2025 12:00:01 A. hardcover. Very Good. 0.8700 in x 9.0000 in x 6.0000 in.
Ask the seller a question Add to wish list
A$52.03
A$5.77 Delivery within USA
Standard delivery: 2 to 8 days
More delivery options
Ships from Suffolk Books Inc (New York, United States)
The BIBLIO Guarantee

Details

  • Title Computational Approaches In Molecular Interaction Analysis: Predicting Protein Complexes, Host-pathogen Interactions, And Protein Function From Interactome Data
  • Author Limsoon Wong (Editor)
  • Binding Hardback
  • Condition Used - Very good
  • Pages 300
  • Volumes 1
  • Language ENG
  • Publisher WSPC
  • Publication date 2/25/2025 12:00:01 A
  • Bookseller's Inventory # mon0000003911
  • ISBN 9789819807178 / 9819807174
  • Weight 1.26 lbs (0.57 kg)
  • Dimensions 9 x 6 x 0.69 in (22.86 x 15.24 x 1.75 cm)
  • Size 0.8700 in x 9.0000 in x 6.0000 i
  • Category Science
  • Quantity available 1

About Suffolk Books Inc New York, United States

Biblio member since 2021

Used Book sellers for over 20 years

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Suffolk Books Inc

Reader reviews for Computational Approaches In Molecular Interaction Analysis: Predicting Protein Complexes, Host-pathogen Interactions, And Protein Function From Interactome Data

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

This book presents a curated collection of research articles from the Journal of Bioinformatics and Computational Biology, highlighting advances in protein-protein interaction-based computational methods for predicting protein complexes, host-pathogen interactions (HPIs), and protein functions. In Part I, it addresses the dynamic challenges of protein complex prediction using innovative techniques like GECA and IPC-RPIN, which integrate network topology, gene expression, and GO annotations to improve accuracy, especially for small complexes. Part II focuses on HPIs, reviewing computational approaches, predictive models, and tools that enhance understanding of infectious diseases, with a particular emphasis on machine learning applications. Part III delves into protein function prediction, employing PPI networks, multi-label methods, and iterative models that account for dynamic interactions. Collectively, these studies provide a comprehensive resource for advancing computational biology and understanding cellular and disease mechanisms.

Please wait a moment while we load the requested page.

tracking-