Department of Computer Science

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https://hdl.handle.net/10919/19035
The Department of Computer Science has an accredited undergraduate program that offers specialized ‘tracks’ of study in key areas. Undergraduates are prepared by graduation for pursuing a computing career or for graduate study. Our active corporate partners program offers internships and permanent employment to our students. Students are encouraged to participate in research experiences during their studies. Capstone courses provide significant team project experiences. The graduate program offers M.S. and Ph.D. degrees, emphasizing thesis work both at the main campus in Blacksburg and at the Northern Virginia Center. About two-thirds of the graduate students are pursuing the Ph.D. degree. The faculty, among whom there are 12 NSF or DOE CAREER Award winners, are active researchers who are visible contributors to the profession and have achieved significant honors.

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Browsing Department of Computer Science by Department "Biochemistry"

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    CMGSDB: integrating heterogeneous Caenorhabditis elegans data sources using compositional data mining
    Pati, Amrita; Jin, Ying; Klage, Karsten; Helm, Richard F.; Heath, Lenwood S.; Ramakrishnan, Naren (Oxford University Press, 2008-01-01)
    CMGSDB (Database for Computational Modeling of Gene Silencing) is an integration of heterogeneous data sources about Caenorhabditis elegans with capabilities for compositional data mining (CDM) across diverse domains. Besides gene, protein and functional annotations, CMGSDB currently unifies information about 531 RNAi phenotypes obtained from heterogeneous databases using a hierarchical scheme. A phenotype browser at the CMGSDB website serves this hierarchy and relates phenotypes to other biological entities. The application of CDM to CMGSDB produces ‘chains’ of relationships in the data by finding two-way connections between sets of biological entities. Chains can, for example, relate the knock down of a set of genes during an RNAi experiment to the disruption of a pathway or specific gene expression through another set of genes not directly related to the former set. The web interface for CMGSDB is available at https://bioinformatics.cs.vt.edu/cmgs/CMGSDB/, and serves individual biological entity information as well as details of all chains computed by CDM.
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    Connecting the Dots between PubMed Abstracts
    Hossain, M. Shahriar; Gresock, Joseph; Edmonds, Yvette M.; Helm, Richard F.; Potts, Malcolm; Ramakrishnan, Naren (PLOS, 2012-01-03)
    Background There are now a multitude of articles published in a diversity of journals providing information about genes, proteins, pathways, and diseases. Each article investigates subsets of a biological process, but to gain insight into the functioning of a system as a whole, we must integrate information from multiple publications. Particularly, unraveling relationships between extra-cellular inputs and downstream molecular response mechanisms requires integrating conclusions from diverse publications. Methodology We present an automated approach to biological knowledge discovery from PubMed abstracts, suitable for “connecting the dots” across the literature. We describe a storytelling algorithm that, given a start and end publication, typically with little or no overlap in content, identifies a chain of intermediate publications from one to the other, such that neighboring publications have significant content similarity. The quality of discovered stories is measured using local criteria such as the size of supporting neighborhoods for each link and the strength of individual links connecting publications, as well as global metrics of dispersion. To ensure that the story stays coherent as it meanders from one publication to another, we demonstrate the design of novel coherence and overlap filters for use as post-processing steps. Conclusions We demonstrate the application of our storytelling algorithm to three case studies: i) a many-one study exploring relationships between multiple cellular inputs and a molecule responsible for cell-fate decisions, ii) a many-many study exploring the relationships between multiple cytokines and multiple downstream transcription factors, and iii) a one-to-one study to showcase the ability to recover a cancer related association, viz. the Warburg effect, from past literature. The storytelling pipeline helps narrow down a scientist's focus from several hundreds of thousands of relevant documents to only around a hundred stories. We argue that our approach can serve as a valuable discovery aid for hypothesis generation and connection exploration in large unstructured biological knowledge bases.
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    Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis
    Dalloul, Rami A.; Long, Julie A.; Zimin, Aleksey V.; Aslam, Luqman; Beal, Kathryn; Blomberg, Le Ann; Bouffard, Pascal; Burt, David W.; Crasta, Oswald; Crooijmans, Richard P. M. A.; Cooper, Kristal; Coulombe, Roger A.; De, Supriyo; Delany, Mary E.; Dodgson, Jerry B.; Dong, Jennifer J.; Evans, Clive; Frederickson, Karin M.; Flicek, Paul; Florea, Liliana; Folkerts, Otto; Groenen, Martien A. M.; Harkins, Tim T.; Herrero, Javier; Hoffmann, Steve; Megens, Hendrik-Jan; Jiang, Andrew; de Jong, Pieter; Kaiser, Pete; Kim, Heebal; Kim, Kyu-Won; Kim, Sungwon; Langenberger, David; Lee, Mi-Kyung; Lee, Taeheon; Mane, Shrinivasrao P.; Marcais, Guillaume; Marz, Manja; McElroy, Audrey P.; Modise, Thero; Nefedov, Mikhail; Notredame, Cédric; Paton, Ian R.; Payne, William S.; Pertea, Geo; Prickett, Dennis; Puiu, Daniela; Qioa, Dan; Raineri, Emanuele; Ruffier, Magali; Salzberg, Steven L.; Schatz, Michael C.; Scheuring, Chantel; Schmidt, Carl J.; Schroeder, Steven; Searle, Stephen M. J.; Smith, Edward J.; Smith, Jacqueline; Sonstegard, Tad S.; Stadler, Peter F.; Tafer, Hakim; Tu, Zhijian Jake; Van Tassell, Curtis P.; Vilella, Albert J.; Williams, Kelly P.; Yorke, James A.; Zhang, Liqing; Zhang, Hong-Bin; Zhang, Xiaojun; Zhang, Yang; Reed, Kent M. (PLOS, 2010-09-01)
    A synergistic combination of two next-generation sequencing platforms with a detailed comparative BAC physical contig map provided a cost-effective assembly of the genome sequence of the domestic turkey (Meleagris gallopavo). Heterozygosity of the sequenced source genome allowed discovery of more than 600,000 high quality single nucleotide variants. Despite this heterozygosity, the current genome assembly (,1.1 Gb) includes 917 Mb of sequence assigned to specific turkey chromosomes. Annotation identified nearly 16,000 genes, with 15,093 recognized as protein coding and 611 as non-coding RNA genes. Comparative analysis of the turkey, chicken, and zebra finch genomes, and comparing avian to mammalian species, supports the characteristic stability of avian genomes and identifies genes unique to the avian lineage. Clear differences are seen in number and variety of genes of the avian immune system where expansions and novel genes are less frequent than examples of gene loss. The turkey genome sequence provides resources to further understand the evolution of vertebrate genomes and genetic variation underlying economically important quantitative traits in poultry. This integrated approach may be a model for providing both gene and chromosome level assemblies of other species with agricultural, ecological, and evolutionary interest.