BOL: Related items

Troyanskaya Lab

Fri, 18 Oct 2013 10:57:40 -0500

In our research, we combine computational methods with an experimental component in a unified effort to develop comprehensive descriptions of genetic systems of cellular controls, including those whose malfunctioning becomes the basis of genetic disorders, such as cancer, and others whose failure might produce developmental defects in model systems.

Research Interest
Genomic Data Integration

Microarray Analysis

Gene and Protein Function Prediction

Detection and Analysis of Chromosomal Abnormalities and Functional Evolution

Integration of Computation and Experiments

Identification of Biological Networks and Pathways

Evaluation and Validation of Computational Predictions

Scalable Visualization-Based Data Analysis

More @ http://reducio.princeton.edu/cm/
PI page @ http://reducio.princeton.edu/cm/ogt

Liberles Research Group

Wed, 12 Aug 2026 03:39:53 -0500

The Liberles Research Group works in the areas of computational comparative genomics, and molecular evolution. The central theme in the research group is the detection and characterization of the lineage-specific divergence of protein-encoding genes. Much of the work in the group is done in a phylogenetic context. Ultimately, we want to ask the question, “What makes each species unique at the genomic level?” and “what are the processes driving the functional divergence of genomes?”.

More at https://sites.temple.edu/liberles/

Computational Genomics Research Lab

Wed, 16 Sep 2026 03:22:38 -0500

The lab is located at the Data Science and AI division, Department of Computer Science and Engineering, University of Gothenburg and Chalmers University of Technology, Sweden. We are also affiliated with Science for Life Laboratory, SciLifeLab.

Our Research: Our lab conduct research at the cutting edge of computational biology and bioinformatics. We aim to understand human genome variation and evolution across different genomic regions by developing interpretable and efficient methods in comparative pan-genomics, leveraging machine learning methods and statistical analysis.

More at https://cgrlab.github.io/

Statistics of current Sequencing and Bioinformatics market

Rahul Agarwal — Wed, 21 Aug 2013 08:29:21 -0500

This survey conducted by Oxford Gene Technology, provider of innovative genetics research and biomarker solutions to advance molecular medicine, has released the results from a recent survey of researchers using next generation sequencing. (Source:http://www.news-medical.net/news/20130821/Oxford-Gene-Technology-releases-next-generation-sequencing-survey-results.aspx )

Address of the bookmark: http://www.ogt.com/assets/0000/3190/NGS_Survey_2013_Infographic_Web.pdf

Following the scientific literature: A personal practical guide for young computational biologists

Rahul Agarwal — Fri, 23 Aug 2013 07:18:51 -0500

The goal of this guide is to describe why, when, where and how can you follow the most up-to-date science of interest and what papers/journals you should follow. The guide is biased towards the fields of genomics/systems biology.(from article)

Source: Igor Ulitsky & Ron Shamir

Address of the bookmark: http://acgt.cs.tau.ac.il/guides/LiteratureGuide.htm

Application Scientist in Strand LifeSciences Bangalore

Mon, 07 Apr 2014 08:17:32 -0500

Job Description
We are looking for a motivated application scientist to help evaluate, compare, and develop next generation sequencing (NGS) data analysis methods. The successful candidate should be able to quickly understand the state-of-art computational biology techniques, prototype them and perform benchmarking studies. The candidate must also be comfortable working with people from different disciplines and be able to present data analysis results in a clear and effective manner. The candidate is also expected to interact with customers as needed, write technical reports and publish new methods and/or data analysis findings in public forums.

Candidate Requirements:
A PhD in computer science, computational biology, Bioinformatics, or a related field, along with sufficient programming skills for prototyping. Experience with next generation sequencing data analysis is required. Candidates with MS degree but with relevant work experience can also be considered.

To Apply
To apply, please send your updated CV and cover letter to Dr. Rohit Gupta (rohit@strandls.com).

Source: http://www.strandls.com/application-scientist

Assistant Professor @ King Saud University Riyadh

Fri, 21 Feb 2014 05:57:18 -0600

Qualifications: Candidates must have a Ph.D. and a strong background in Molecular and Cellular Biology, protein expression, FACS, or computational biology, and ability to work collaboratively.

This position will have a significant focus on providing analytical support for next generation sequencing data analysis – Exome-sequencing, Targetted sequencing as well as high-throughput genotyping on Illumina platform.

Job location:

Genome Research Chair
King Saud University, Riyadh-11451
KSA

Interested candidate may forward their CV to grcksu@gmail.com

J. Aires de Sousa Research Group

Wed, 12 Mar 2014 09:57:25 -0500

We are involved in the development of methods and software in chemoinformatics. Current main projects are:

1.automatic learning of chemical reactivity and metabolism,
2.simulation of NMR spectra,
3.modelling of properties of ionic liquids, and
4.representation of molecular chirality.

More at http://joao.airesdesousa.com/

Amity University Bioinformatics Summer Program - Kolkata

eliabrodsky — Tue, 11 Jun 2019 21:27:10 -0500

Registrations are now open for the 2019 Summer Bioinformatics Training program at Amity University, Kolkata. The program will focus on introductory topics for life science students. We will review important history, topics and challenges bioinformatics can help address in the context of basic research, discovery and industry.

Read more: https://edu.t-bio.info/amity-university-summer-bioinformatics-program-registrations-are-open/

Gerstein Lab

Wed, 19 Mar 2014 12:48:20 -0500

The focus of the Gerstein Lab is interpreting personal genomes, particularly in relation to disorders, such as cancer. This endeavor has a number of related aspects described below. Moreover, the approaches we take have broad connections to a variety of data-intensive fields, within the emerging discipline of data science.

Personal Genome Variation: SVs
Human Genome Annotation: Processing Next-Gen Sequencing Data
Comparative Genomics: Pseudogenes as Molecular Fossils
Protein Structure and Function: Macromolecular Motions
Analysis of Diverse Networks
Genomics at the Forefront of Data Science

Lab page: http://www.gersteinlab.org/