JRF Bioinformatics
Eligibility : ME/M.Tech(Bio-Informatics/Bio-Chemistry Engg), MSc(Bio-Informatics)
Location : Hyderabad
Last Date : 30 Dec 2015
Hiring Process : Written-test
University of Hyderabad
JRF Bioinformatics job position...
3 PhD positions available in the area of Bioinformatics/Computational Biology, Machine Learning (ML)/Artificial Intelligence (AI), Biomarker Discovery, Stratified/Personalized Medicine in Mental Health, Diabetes and Multimorbidity. Please see...
CSIR-Institute of Genomics & Integrative Biology (IGIB) is a premier Institute of Council of Scientific
and Industrial Research (CSIR), engaged in research of national importance in the areas of genomics,
molecular medicine, bioinformatics and...
Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.
Professionally, Python is great for backend web development, data analysis, artificial...
Shirley is a computational biologist with expertise in cancer epigenetics. Her research focuses on algorithm development and integrative mining from big data generated on microarrays, massively parallel sequencing, and other high throughput...
journals.plos.org - By taking a comprehensive and careful approach to deep learning based on critical thinking about research questions, planning to maintain rigor, and discerning how work might have far-reaching consequences with ethical dimensions, the life science...
www.sbgenomics.com - Seven Bridges is the biomedical data analysis company accelerating breakthroughs in genomics research for cancer, drug development and precision medicine. We build self-improving systems to analyze millions of genomes, including the Graph...
github.com - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.
DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation...
github.com - Achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels. In this paper, we present GraphPath, a biological knowledge-driven...