BOL: Related items

04- Informatics Approach to Cancer - Interview with Dr. Joel Saltz

Mon, 07 Oct 2013 14:35:43 -0500

For additional information visit http://www.cancerquest.org/joel-saltz-interview. Dr. Joel Saltz is a Professor in the Departments of Pathology, Biostatistics and Bioinformatics, and Mathematics and Computer Science at Emory University. Dr. Saltz's research on bioinformatics spans several disciplines. One project involves applying computer analysis to medical imaging to yield better results for patients. As an example, a computer program may able to help doctors detect small cancers in a CT scan or mammogram. In this interview segment, Dr. Saltz discusses the informatics approach to cancer. To learn more about cancer and watch additional interviews, please visit the CancerQuest website at http://www.cancerquest.org.

Evolution and Cancer

Fri, 27 Sep 2013 11:28:49 -0500

Air date: Wednesday, January 04, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Category: Wednesday Afternoon Lectures Description: There is a broad consensus that cancer is the result of somatic cells having serially gained, by a series of mutations, the ability to grow independently, to recruit resources from the circulation and the stroma, to invade local tissues, and to found anatomically distant metastases, ultimately killing the host. From the point of view of the cancer-causing somatic cell population, this is evolution driven by mutation and selection. Genomics has resulted in a parallel consensus that the central functions of all eukaryotes are highly conserved, not only at the level of individual protein functions, but also complex biological pathways and systems. These ideas motivated a comparison between results of molecular genetic studies of experimental evolution in yeast and the molecular genetic phenomena associated with tumorigenesis and tumor progression. We find some very striking similarities, including recurring genomic rearrangements, alterations of the regulation of specific growth-promoting genes, population-genetic features that affect the fitness trajectories of growth rate variants in evolving populations, and physiological and metabolic similarities derived from the conservation of the basic plan of growth and cell multiplication among all eukaryotes. It is hoped that some of the insights from yeast will aid the interpretation of sequence changes found in tumors, especially in the urgent necessity to distinguish 'driver' from 'passenger' mutations." David Botstein's fundamental contributions to modern genetics include the development of genetic methods for understanding biological functions and the discovery of the functions of many yeast and bacterial genes. In 1980, Botstein and three colleagues proposed a method for mapping human genes that laid the groundwork for the Human Genome Project. The basic principle of the mapping scheme was to develop, by recombinant DNA techniques, random single-copy DNA probes capable of detecting DNA sequence polymorphisms when hybridized to restriction digests, or specific fragments, of an individual's DNA. The method was used in subsequent years to identify several human disease genes, such as Huntington's and BRCA1. Variations of this method enabled the sequencing phase of the Human Genome Project. In the 1990s Botstein, having moved to Stanford University School of Medicine, collaborated with Patrick O. Brown of Stanford in exploiting DNA microarrays to study genome-wide gene expression patterns in yeast and in human cancers. This required developing a new statistical method and graphical interface, widely used today to interpret genomic data. Botstein also has helped to create, with Michael Ashburner and Gerald Rubin, a bioinformatics initiative to unify the representation of gene and gene product attributes across all species, called Gene Ontology. He graduated from Harvard College and earned his doctorate from the University of Michigan. He worked at Massachusetts Institute of Technology from 1967 to 1988; served as vice president for science at Genentech from 1988 to 1990; chaired the Department of Genetics at the Stanford University School of Medicine from 1990 to 2003; and joined the Princeton University faculty in 2003. He has sat on numerous editorial boards and was the founding editor of Molecular Biology of the Cell. Among recent major awards, Bostein won the Peter Gruber Foundation Prize in Genetics in 2003, the Apple Science Innovator Award in 2008, and the Albany Medical Center Prize in 2010. The NIH Wednesday Afternoon Lecture Series includes weekly scientific talks by some of the top researchers in the biomedical sciences worldwide. For more information, visit: The NIH Director's Wednesday Afternoon Lecture Series Author: Dr. David Botstein, Princeton University Runtime: 00:59:58 Permanent link: http://videocast.nih.gov/launch.asp?17046

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/

BOKU Lab

Wed, 08 Jan 2014 19:33:12 -0600

We are interested in the study of complex systems in living organisms. Novel views augmenting the classical gene by gene approaches are required to overcome the engineered redundancies and combinatorial effects prevalent in higher eukaryotes. We therefore combine work to establish improved quantitative experimental assays, such as microarrays or differential in-gel electrophoresis, and development of modern computational methods, such as hierarchical probabilistic models or integration of heterogeneous data sources, focussed by biological studies in our laboratory and collaborations.

Highlights of our research include:

Optimization of microarray design, probe signal interpretation
Advanced models and tools for expression profiling
State-of-the-art applications and integrated analyses

Lab page @ http://bioinf.boku.ac.at/

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/

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/