180-word research description

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We do research in bioinformatics, applying computational approaches to problems in molecular biology. Broadly, we are interested in large-scale analyses of genome sequences, macromolecular structures, and functional-genomics datasets. It is hoped that these will allow us to address a number of overall statistical questions about macromolecules, relating to their physical properties, cellular function, interactions, and phylogenetic distribution. We are especially focused on the human genome and proteome. Our research involves a number of quantitative techniques, including database design, systematic datamining and machine learning, visualization of high-dimensional data, and molecular simulation. More specifically, we focus on three questions. First, we are interested in annotating the raw human genome sequence, especially in characterizing the vast intergenic regions. Next, we are trying to get at the function of all the genes encoded by the genome. Here, we try to characterize function on a large-scale through the use of molecular networks. Finally, for the group of protein-coding genes that have known 3D structures, we are trying to see how their function is carried out through motion and how motion can be predicted from packing geometry.
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We do research in bioinformatical data science, applying computational approaches to problems in molecular biology. Broadly, we are interested in large-scale analyses of genome sequences and macromolecular structures. We also work on the analysis of images and large-scale text and sensor data. We are especially focused on the human genome and proteome and phenotype descriptions associated with them. Our research involves a number of quantitative techniques, including database design, systematic data mining and deep learning, visualization of high-dimensional data, and molecular simulation. More specifically, we focus on three questions. First, we are interested in annotating the raw human genome sequence, especially in characterizing the vast intergenic regions. Next, we are trying to get at the function of all the genes encoded by the genome. Here, we try to characterize function on a large-scale through the use of molecular networks. Finally, for the group of protein-coding genes that have known 3D structures, we are trying to see how their function is carried out through motion and how motion can be predicted from packing geometry.
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(7-Dec-2015, 181 words)
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(1-Dec-2019, 173 words)
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[http://info.gersteinlab.org/index.php?title=180-word_research_description&oldid=3785 (Older, 2015 version)]

Latest revision as of 19:58, 1 December 2019

We do research in bioinformatical data science, applying computational approaches to problems in molecular biology. Broadly, we are interested in large-scale analyses of genome sequences and macromolecular structures. We also work on the analysis of images and large-scale text and sensor data. We are especially focused on the human genome and proteome and phenotype descriptions associated with them. Our research involves a number of quantitative techniques, including database design, systematic data mining and deep learning, visualization of high-dimensional data, and molecular simulation. More specifically, we focus on three questions. First, we are interested in annotating the raw human genome sequence, especially in characterizing the vast intergenic regions. Next, we are trying to get at the function of all the genes encoded by the genome. Here, we try to characterize function on a large-scale through the use of molecular networks. Finally, for the group of protein-coding genes that have known 3D structures, we are trying to see how their function is carried out through motion and how motion can be predicted from packing geometry.

(1-Dec-2019, 173 words)

(Older, 2015 version)

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