Computational biology and applied bioinformatics

✍ Scribed by Lopes, Heitor Silverio; Cruz, Leonardo Magalhães (eds.)

• Publisher: InTech
• Year: 2011
• Tongue: English
• Leaves: 456
• Category: Library

✦ Table of Contents

Content: Molecular evolution & phylogeny: what, when, why & how? --
Understanding protein function --
the disparity between bioinformatics and molecular methods --
In silico identification of regulatory elements in promoters --
In silico analysis of Golgi glycosyltransferases: a case study on the LARGE-like protein family --
Microarray technology --
expression profiling of MRNA and MicroRNA in breast cancer --
Computational tools for identification of microRNAs in deep sequencing data sets --
Computational methods in mass spectrometry-based protein 3D studies --
Synthetic biology & bioinformatics prospects in the cancer arena --
An overview of hardware-based acceleration of biological sequence alignment --
Retrieving and categorizing bioinformatics publications through a multiagent system --
GRID computing and computational immunology --
A comparative study of machine learning and evolutionary computation approaches for protein secondary structure classification --
Functional analysis of the cervical carcinoma transcriptome: networks and new genes associated to cancer --
Number distribution of transmembrane helices in prokaryote genomes --
Classifying TIM barrel protein domain structure by an alignment approach using best hit strategy and PSI-BLAST --
Identification of functional diversity in the enolase superfamily proteins --
Contributions of structure comparison methods to the protein structure prediction field --
Functional analysis of intergenic regions for gene discovery --
Prediction of transcriptional regulatory networks for retinal development --
The use of functional genomics in synthetic promoter design --
Analysis of transcriptomic and proteomic data in immune-mediated diseases --
Emergence of the diversified short ORFeome by mass spectrometry-based proteomics --
Acrylamide binding to its cellular targets: insights from computational studies.

✦ Subjects

Computational Biology.