denbi-metagenomics-workshop.readthedocs.io - Welcome to the one-day metagenomics assembly workshop. This tutorial will guide you through the typical steps of metagenome assembly and binning.
The Tutorial Data Set
FastQC Quality Control
Assembly
Velvet Assembly
MEGAHIT...
Pattern recognition and computational biology
MEME Suite software development; gene expression; mathematical modelling; gene regulation and transcription
Specialization:
Pattern recognition and modelling in computational biology
Link @...
en.wikipedia.org - FASTQ format is a text-based format for storing both a biological sequence (usually nucleotide sequence) and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a...
Bioinformatics Infrastructure Facility
University of Madras
Chennai 600 025
Applications are invited for the STUDENTSHIP and TRAINEESHIP vacancies to carry out project/research work in the DBT - Bioinformatics Infrastructure Facility with...
scilifelab.github.io - SciLifeLab is a national center for molecular biosciences with focus on health and environmental research.
Courses
Old courses (2012-2014)
Metagenomics Workshop
2015 November - Uppsala2016 November - Uppsala2017 November - Uppsala
Introduction...
Computer Aided Protein Structure Prediction; Identification of Vaccine
Candidates (T-Epitope prediction); Analysis of Nucleotide/Protein Sequences; Development of Web Server/
Software; Creation of Public Domain Resources in Biology
Present...
The 3rd Annual Next Generation Sequencing Asia Congress is to be held on the 22nd and 23rd of October 2013 in Singapore. Over the 2 days, the conference will provide an overview of the current options of next-generation sequencing platforms,...
RASA conducts comprehensive Life Science skill development training courses in Pune, India for working professionals, researchers, students and job-seeker. The trainings are crafted meticulously, covering different modules of courses such as...
homes.sice.indiana.edu - Machine learning techniques have been successful in analyzing biological data because of their capabilities in handling randomness and uncertainty of data noise and in generalization. In this class, we will learn basics about probabilistic models...