BOL: Related items

Translational Bioinformatics: Transforming 300 Billion Points of Data

Tue, 20 Aug 2013 19:03:47 -0500

Translational Bioinformatics: Transforming 300 Billion Points of Data into Diagnostics, Therapeutics, and New Insights into Disease Air date: Wednesday, June 20, 2012, 3:00:00 PM Time displayed is Eastern Time, Washington DC Local Description: There is an urgent need to translate genome-era discoveries into clinical utility, but the difficulties in making bench-to-bedside translations haven't been well described. The nascent field of translational bioinformatics may help. Dr. Butte's lab at Stanford University builds and applies tools that convert more than 300 billion points of molecular, clinical, and epidemiological data (measured by researchers and clinicians over the past decade) into diagnostics, therapeutics, and new insights into disease. Dr. Butte, a bioinformatician and pediatric endocrinologist, will highlight his lab's work on using publicly available molecular measurements to find new uses for drugs, discovering new treatable mechanisms of disease in type 2 diabetes, and evaluating patients presenting with whole genomes sequenced. 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: Atul Butte, M.D., Ph.D., Stanford University Runtime: 01:07:42 Permanent link: http://videocast.nih.gov/launch.asp?17321

Chang lab

Tue, 24 Sep 2013 17:25:49 -0500

The Chang lab is focused on how the activities of hundreds or even thousands of genes (gene parties) are coordinated to achieve biological meaning. We have pioneered methods to predict, dissect, and control large-scale gene regulatory programs; these methods have provided insights into human development, cancer, and aging. A particular interest is how cells know and remember their locations in the body, particularly with the help of long noncoding RNAs.

More at http://changlab.stanford.edu/index.html

Tijana Milenkovic Lab

Fri, 30 Aug 2013 06:45:20 -0500

Complex networks and network mining: developing graph theoretic, mathematical, and computational algorithms for efficient extraction of function from topology of complex real-world networks, such as biological, social, and technological networks.

Computational and systems biology: studying the interplay between network topology and biological function, disease, and evolution in molecular (e.g., protein-protein interaction) networks.

Computational chemistry: protein folding; computational drug discovery and design.

Synthetic biology.

More at http://www.cse.nd.edu/~tmilenko/index.html

Huber Lab

Mon, 09 Sep 2013 21:57:03 -0500

The Huber group develops computational and statistical methods to design and analyse novel experimental approaches in genetics and cell biology.

Future projects and goals

Large-scale systematic maps of gene-gene and gene-environment interactions by automated phenotyping, using image analysis, machine learning, sparse model building and causal inference.
DNA-, RNA- and ChIP-Seq and their applications to gene expression regulation: statistical and computational foundations.
Cancer genomics, genomes as biomarkers, cancer phylogeny.
Image analysis for systems biology: measuring the dynamics of cell cycle and of cell migration of individual cells under normal conditions and many different perturbations (RNAi, drugs).

More @ http://www.embl.de/research/units/genome_biology/huber/index.html

Giovanni Parmigiani Lab

Fri, 20 Sep 2013 13:21:41 -0500

Scientific Interests:

Models and software for predicting who is at risk of carrying genetic variants that confer susceptibility to cancer. Application to breast, ovarian, colorectal, pancreatic and skin cancer.

Statistical methods for the analysis of high throughput genomic data: analysis of cancer genome sequencing projects; integration of genomic information across technologies; cross-study validation of genomics results.

Statistical methods for comparative effectiveness research: comprehensive models for lifetime history of chronic disease outcomes; Bayesian meta-analysis; Bayesian causal inference; decision analysis.

Bayesian modeling and computation: multilevel models; decision theoretic approaches to inference; sequential experimental design and their application to adaptive and multistage studies in clinical and epidemiological research.

http://bcb.dfci.harvard.edu/~gp/index.html

http://scholar.google.com/citations?user=OlpYP3UAAAAJ&hl=en

Vvek's Lab

Thu, 26 Sep 2013 11:11:39 -0500

Broad Area of Research: RNA biology (microRNA, lncRNA), Stem cells, Functional genomics, Epigenomics and Cancer

RNAs, especially non-coding RNAs (such as microRNA, long ncRNAs) are recently identified to be very abundant in mammalian organisms and play some key roles in gene expression regulation, gene silencing, and also implicated in disease progression, stem cell pluripotency etc. Current research activities of our lab include analysis of expression pattern of ncRNAs by microarray and next-gen sequencing data and understanding the role of miRNAs or other regulatory RNAs in various diseases, especially cancer and validation by reporter assays (renilla/luciferase) and other experimental tools.

More @ http://vvekslab.in/index.html

Programming language to build synthetic DNA

Jit — Mon, 30 Sep 2013 16:37:24 -0500

A team led by Georg Seelig (http://homes.cs.washington.edu/~seelig/index.html) at University of Washington has developed a programming language for chemistry that it hopes will streamline efforts to design a network that can guide the behavior of chemical-reaction mixtures in the same way that embedded electronic controllers guide cars, robots and other devices. In medicine, such networks could serve as “smart” drug deliverers or disease detectors at the cellular level.

Reference & More @

http://www.nature.com/nnano/journal/vaop/ncurrent/full/nnano.2013.189.html

http://www.washington.edu/news/2013/09/30/uw-engineers-invent-programming-language-to-build-synthetic-dna/

Image source: washington.edu

Mike Ritchie Lab

Wed, 02 Oct 2013 15:25:45 -0500

Mike Ritchie Lab primary research focus is the detection of susceptibility genes for common diseases such as cancer, diabetes, hypertension, and cardiovascular disease, among others. The approaches will involve the development and application of new statistical methods with a focus on the detection of gene-gene interactions associated with human disease.

Gene expression and protein expression patterns between normal and non-normal tissues is a growing area of research that may lead to the identification of candidate genes for understanding the etiology of common, complex diseases.

Lab homepage @ http://ritchielab.psu.edu/ritchielab/

Yau Group

Tue, 15 Oct 2013 13:05:15 -0500

Yau Group are a new research group based at the Wellcome Trust Centre for Human Genetics and the Department of Statistics at the University of Oxford.

Yau Group develops statistical and computational methods for the analysis of genomic datasets with a particular interest in cancer sequencing applications and the use of Bayesian Statistics.

Yau Group are currently have projects in somatic mutation analysis of heterogeneous cancers, data fusion or integration techniques and single cell genomics.

More @ http://www.well.ox.ac.uk/~cyau/index.html

Computational Methods for the Analysis of the Diversity and Dynamics of Genomes

Sat, 09 Nov 2013 20:19:02 -0600

The German-Canadian international research training group

"Computational Methods for the Analysis of the Diversity and Dynamics of Genomes"

has currently open positions for graduate students, to study at Simon Fraser University (Vancouver, Canada) and
Bielefeld University (Germany), starting in the fall 2014.

This international graduate program is a close cooperation of:

Bielefeld University, Germany: Graduate progam "DiDy"
Simon Fraser University (SFU), Vancouver, Canada: Graduate program "MADD-Gen"

The available positions include six PhD positions at Bielefeld University, as well as PhD and MSc positions at SFU.

Application deadline: December 31st, 2013
Webpage: http://wiki.techfak.uni-bielefeld.de/didy/Announcement