Graduate Student

mpop's picture

Visiting Research Scientist

New metagenomic assembler published by CBCB scientists

Tue Jan 15, 2013

A paper describing the metAMOS software, a new metagenomic assembly and analysis pipeline, has appeared in the journal Genome Biology. This project, initiated in Dr. Mihai Pop's lab, was led by Dr. Todd Treangen, a former postdoctoral fellow in our center, and currently a researcher at NBACC in Frederick, Maryland. The research team includes a number of current and former members of the CBCB as well as other collaborators from NBACC and the University of California, Davis.

OMICS Day: Next Generation Biology at UM

OMICS Day provides a unique and premier forum to learn about the high throughput “systems” biology research at University of Maryland, to foster new synergistic partnerships, and to contemplate future directions.

Collaborative Research: Phylogeny of Lepidoptera

This collaborative, multi-disciplinary project will exploit recent progress in genomics - the study of the complete genetic content of species and how it works - to greatly advance our knowledge of evolutionary relationships in the insect order Lepidoptera (moths and butterflies). A broad-scale "family tree" (phylogeny, genealogy) will be estimated using DNA sequences from approximately 250 species, representing all 126 families into which Lepidoptera are currently divided.

Principal Investigators

III: Small: Genome Assembly Using Sparse Sequence Info

Rapid advances in DNA sequencing technologies are providing scientists with the ability to rapidly and cost-effectively decode the genomes of organisms. Current technologies, however, can only reconstruct a fragmented picture of a genome's chromosomes. Stitching the resulting fragments together into a complete genome currently requires costly and time-intensive laboratory experiments.

Principal Investigators

Better Network Modules: New Tools for Protein Network Analysis

The University of Maryland College Park is awarded a grant to develop new algorithms and a suite of software tools based on a general and flexible definition of a ""network module"" in order to extract meaningful biological clusters from noisy and incomplete protein-protein interaction data. Recently developed high-throughput techniques are being used to sample protein-protein interactions from many organisms and are creating a wealth of data that must be analyzed computationally.

Principal Investigators

Algorithms for the Analysis of Data from Massively-parallel Genome Sequencing

New generation DNA sequencing technologies are revolutionizing modern biological research. Scientists can now generate the rough equivalent of an entire human genome (~3 billion base-pairs of DNA) in just a few days with one single sequencing instrument. Until recently, such amounts of data could only be generated at large genome centers using hundreds of sequencers. The analysis of these data is complicated by their size - a single run of a sequencing instrument yields terabytes of information, often requiring a significant scale-up of the existing computational infrastructure.

Principal Investigators

Graphs to Diversity: Extracting Genomic Variation from Sequence Graphs

Recent advances in genome sequencing technologies have enabled the sequencing of bacteria directly from the environment, providing a broader outlook on the diversity of bacteria than ever before possible. Recent studies of environmental samples have revealed complex communities containing many previously unknown species, and uncovered a large amount of genetic variation and diversity even among closely related strains.

Principal Investigators

Pages

Subscribe to CBCB RSS