https://www.ncbi.nlm.nih.gov/research/coronavirus/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/research/coronavirus/

The best part about the DBT-BET Exam is both the question paper & answer key is released immediately after the exam so you get the upper hand here to check how well you did in the DBT-BET exam, how much you are going to score and if you can pass the Exam with good score. This helps you in planning your career ahead.

DBT Exam is held once in a year by Department of Biotechnology – Govt of India. Candidates willing to get DBT-Junior Research Fellowship – DBT JRF fellowship should take up the  DBT-BET Exam, DBT – Biotechnology Eligibility Test (BET) 2020 to be held on somewhere in the month of April. Official Notification for DBT-BET 2020 will be released in Feb 2020.

Question at https://bioinformaticsonline.com/file/view/39260/biotechnology-eligibility-test-bet-question-paper

Results from computer simulations show that it is energetically less expensive to bend mismatch-containing, defective DNA (G:T, C:C, C:T, G:A, G:G, T:T, A:A, A+:C) vs. non-defective DNA (containing A:T or G:C base pairs). DNA repair mechanisms likely take advantage of this feature to detect defective DNA based on an increased bending propensity.

http://www.tacc.utexas.edu/news/feature-stories/2013/how-dna-repair-helps-prevent-cancer

http://pubs.acs.org/doi/abs/10.1021/jp403127a

More at http://pandeylab.igm.jhmi.edu/

http://scholar.google.com/citations?user=OhuG0FcAAAAJ&hl=en

Job Description: We are interested in finding an excellent postdoc with interests in protein functional annotation, machine learning and computer grids. The position is open for 3.5 years at the Université Pierre et Marie Curie, in the heart of paris.

Research topic: Protein function annotation, multiple probabilistic models, domain architecture, machine learning, combinatorial optimization, computer grid.

Title: A novel integrative platform for large scale protein annotation that exploits a multitude of diversified probabilistic models in several protein signature databases.

We propose a novel integrated approach for large scale protein annotation that will exploit an unprecedented amount of genomic data as well as sophisticated machine learning techniques and combinatorial optimization approaches taking advantages of High Performance Computing (HPC) environments. The idea is to uncover as much as possible the evolutionary processes of protein sequences that took place throughout the whole tree of life and that affected the evolution of a protein family. We have already demonstrated in a previous work that the problem of functional annotation is inherent to the ability of uncovering such paths. Now, we shall extend this approach to large scale genome annotation by considering 11 different protein databases, constituted by about 10^9 protein sequences, and by producing a large pool of diversified probabilistic models coding for about 10^7 evolutionary protein pathways. Such models will be used to search for specific domains in genomes to be annotated. Our previous methodology needs to be fundamentally improved to deal with this large amount of biological data. In this project, we shall work on the algorithms to reduce the space of models and the search complexity, and we shall implement some important algorithmic changes towards the realization of a powerful integrated annotation tool.

Where: This project is run on the Laboratoire de Biologie Computationnelle et Quantitative UMR7238 CNRS-UPMC – Analytical Genomics team, headed by A.Carbone. It is co-advised with Pierre-Henri Wuillemin, Laboratoire d’Informatique de Paris 6 – Equipe DECISION.

Start date: September 1st, 2014
Contact Person: Alessandra Carbone
Contact: alessandra.carbone@lip6.fr

If you are looking for a new opportunity and have skills within any sector of Bioinformatics with an IT skill then I would love to hear from you. I have various exciting opportunities from programmers to researchers to scientists.

Call me now on 01772 278050 or email me your cv and requirements and I will call you back dareen.evans@itworkshealth.co.uk

NO: 340/ESTB/ADMN/NIBMG/2015-16
Doctoral Research In Biomedical Genomics, Including Statistical Genomics conduct National Institute of Biomedical Genomics (NIBMG)
Information For Students Interested To Pursue Doctoral Research In Biomedical Genomics, Including Statistical Genomics, At The National Institute Of Biomedical Genomics (Nibmg), Kalyan
Eligibility conditions for specific areas of research are :
Statistical Genomics : An applicant who wishes to pursue research in Statistical Genomics should hold a Master's degree (First class or equivalent) in a relevant discipline (Statistics, Mathematics, Bioinformatics, or a related discipline)
Biomedical Genomics : An applicant who wishes to pursue research in any area of biomedical genomics, other than statistical genomics, should hold a Master's degree (First class or equivalent) in a relevant discipline (Biochemistry, Biotechnology, Molecular Biology, Genetics, Zoology, Physiology, or a related discipline)
Fellowship : An applicant should have passed the NET conducted by CSIR/UGC/ICMR/DBT within the past ONE year AND should have been awarded a valid Junior Research Fellowship from CSIR, UGC, ICMR, DBT (Category-I only), DST (INSPIRE), NBHM. Preference will be given to candidates with demonstrable research training in the form of summer training or short-term courses in established research laboratories in preparation for a research career in biomedical sciences
How to apply
Online application will be accepted until 5 PM of December 31, 2015. A formal interview of the short-listed candidates will be held on January 12, 2016

More at http://www.nibmg.ac.in/?q=Career%20Opportunities