Research

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Big Data in Bioinformatics

Biology is becoming increasingly data-intensive as high-throughput genomic assays become more accessible to greater numbers of biologists. Working with large-scale data sets requires user-friendly yet powerful software tools that stimulate user's intuition, reveal outliers, detect deeper structures embedded in the data, and trigger insights and ideas for new experiments. To learn more...

Computational Biophysics

While bioinformatics efforts generally involve the classification, archiving, and model building from empirical data sources, computational biophysics is focused on the development of predictive models and simulation techniques based on first principles. Meaning, computational biophysics attempts to develop theoretical models that capture the essential physics, chemistry, and/or biology. To learn more...

Computational Mass Spectrometry

Mass spectrometry has emerged as a key technology for proteomics (the study of the total protein complement of a cell) and metabolomics (comprehensive characterization of the small molecule metabolites in biological systems). Associated with these studies is large volume of complex data. Computational mass spectrometry concerns processing, analyzing, and visualizing the data with the ultimate goal to find biological meaning from the data. To learn more...

Genome-Wide Association Analysis

Genome-Wide Association Studies have the goal of the identifying disease susceptibility genes, especially for conditions to which multiple genes contribute. Such studies use devices that perform parallel measurements of millions of loci simultaneously. Although the experimental design depends on the type of organism and population, in humans these studies involve collecting data from thousands of individuals, sometimes in case-control cohorts, otherwise in family trios. To learn more...

High-Throughput Studies

High-throughput Studies can be considered from two perspectives: there are platforms that measure many datapoints per sample; there are also platforms that measure the response of many samples to one treatment. To learn more...

Metagenomics

Metagenomics is the study of metagenomes, genetic material recovered directly from environmental samples. The broad field may also be referred to as environmental genomics, ecogenomics or community genomics. While traditional microbiology and microbial genome sequencing rely upon cultivated clonal cultures, early environmental gene sequencing cloned specific genes (often the 16S rRNA gene) to produce a profile of diversity in a natural sample. To learn more...

Plant Genomics

Humans rely on plants for food, fuel, fiber, medicine, and building materials. Understanding how plants grow, how they reproduce and evolve, and how plants respond to their environment is essential to humanity's survival on planet earth. We are using methods from bioinformatics and genomics to investigate basic and applied questions in plant biology. To learn more...

Structural Bioinformatics

While biological macromolecules can be described as linear strings based on their sequence, a complete description of how they function and are regulated generally requires more complete structural descriptions. Structural bioinformatics is the subset of bioinformatic efforts related to the archival/retrieval, comparison, and prediction of biological structures. To learn more...

Systems Biology

Traditionally, molecular biologists study the functions of a single molecule in the cell in isolation from its interacting partners. This analytical approach has been successful for understanding the biochemical functions of individual biological molecules, however, it is not likely for this approach to yield a comprehensive understanding of a biological phenomenon, which is the system behvior of a specific set of interacting molecules in the cell, and a biological molecule carry out its functions through interacting with other molecules. To learn more...

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