Name: Computational Approaches in Molecular Interaction Analysis: Predicting Protein Complexes, Host-Pathogen Interactions, and Protein Function From Interactome Data (en Inglés)
Price: 416.47 PEN
Availability: InStock
Author: Limsoon Wong
ISBN: 9789819807178

portada Computational Approaches in Molecular Interaction Analysis: Predicting Protein Complexes, Host-Pathogen Interactions, and Protein Function From Interactome Data (en Inglés)

Computational Approaches in Molecular Interaction Analysis: Predicting Protein Complexes, Host-Pathogen Interactions, and Protein Function From Interactome Data (en Inglés)

Formato

Libro Físico

Editorial

World Scientific Publishing

Autor

Limsoon Wong

Idioma

Inglés

N° páginas

300

Encuadernación

Tapa Dura

ISBN13

9789819807178

Computational Approaches in Molecular Interaction Analysis: Predicting Protein Complexes, Host-Pathogen Interactions, and Protein Function From Interactome Data (en Inglés)

Limsoon Wong (Autor) · World Scientific Publishing · Tapa Dura

Más barato Libro Nuevo Importado

Envío: 14 a 19 días háb.

S/ 925,49S/ 416,47

-55%

Más rápido Libro Nuevo Importado

Envío: 12 a 17 días háb.

S/ 1.027,55S/ 462,40

-55%

Costos de importación incluídos en el precio ✅

Libro Nuevo Más barato

Quedan 100 unidades

S/ 416,47

Llega entre el 27 Ago y el 04 Sep a CERCADO DE LIMA, Lima. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Computational Approaches in Molecular Interaction Analysis: Predicting Protein Complexes, Host-Pathogen Interactions, and Protein Function From Interactome Data (en Inglés)"

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.