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Biomedical research is becoming increasingly data driven, analytical and hence digital. In recognition of this evolution NIH has established the Office for Data Science with trans NIH responsibility for maximizing the value of this digital enterprise. This effort brings together communities, policy changes and new infrastructure to be applied to existing and new areas of research such as precision...
Welcome to the 2015 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2015) being held in the metro Washington DC area, USA, from November 9–12, 2015. On behalf of the IEEE BIBM 2015 Organizing Team, we would like to thank you for your participation and hope you will enjoy the conference.
Millions of bacteria make our bodies their home. They help keep us healthy, and disruptions in the normal microbiota are believed to contribute to a number of diseases. Cost-effective sequencing technologies have made it possible to sequence the genomes of human-associated microbial communities, leading to the birth of a new scientific discipline - metagenomics. Analyzing the resulting data, however,...
Reverse engineering whole-genome networks from large-scale gene expression measurements and analyzing them to extract biologically valid hypotheses are important challenges in systems biology. While simpler models easily scale to large number of genes and gene expression datasets, more accurate models are compute intensive limiting their scale of applicability. In this talk, I will present our research...
Dr. Eric Xing is a Professor of Machine Learning in the School of Computer Science at Carnegie Mellon University, and Director of the CMU/UPMC Center for Machine Learning and Health. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture; especially for solving problems involving automated learning,...
Motivation: The identification and accurate description of large genomic rearrangements is crucial for the study of evolutionary events among species and implicitly defining breakpoints. Although there is a number of software tools available to perform this task, they usually either a) require a collection of pre-computed non-conflicting High Scoring Pairs (HSPs) and gene annotations or involve working...
Protein function is the result of a complex yet precise relationship between protein structure and dynamics. The ability of a protein to assume different structural states is key to biomolecular recognition and function modulation. Protein modeling research is driven by the need to complement experimental techniques in obtaining a comprehensive and detailed characterization of protein equilibrium...
It is well-known that inhibitors of protein kinases bind with very different selectivity profiles. This is also the case for inhibitors of many other protein families. A better understanding of binding selectivity would enhance the design of drugs that target only a subfamily, thereby minimizing possible side-effects. The increased availability of protein 3D structures has made it possible to study...
The identification of interactions between compounds and proteins plays an important role in network pharmacology and drug discovery. However, experimentally identifying compound-protein interactions (CPIs) is generally expensive and time-consuming, computational approaches are thus introduced. Among these, machine-learning based methods have achieved a considerable success. However, due to the nonlinear...
Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal...
Wnt signal transduction pathway (Wnt STP) is a crucial intracellular pathway mainly due to its participation in important biological functions, i.e., embryonic development, and stem-cell management among others as well as in human pathology, mainly cancer. For these very reasons, Wnt STP is one of the highest researched signal transduction pathways. Study and analysis of its origin, expansion and...
Visualization is an important method in microbiome data analysis, and dimensionality reduction is a necessary procedure to achieve it. Multidimensional Scaling (MDS) is a popular method, which is necessary to compute the distance matrix. The Unifrac distance is very reasonable and biologically meaningful in the analysis of microbiome data. Due to the complexity of the phylogenetic tree and the high...
Understanding Protein-protein interaction (PPI) is of fundamental importance in deciphering cellular processes. Predicting PPIs is thus critical in making new discoveries in the biological domains. Traditionally, new PPIs are identified through biochemical experiments but such methods are labor-intensive, expensive, time-consuming and technically ineffective due to high false positive rates. Computational...
Motivation: Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms such as Probabilistic Roadmap Methods (PRMs) have been successful in modeling the protein folding landscape. PRMs and variants contain several phases (i.e., sampling, connection, and path extraction). Global machine learning has been applied to the connection phase but is inefficient...
The longest common subsequence (LCS) problem is a classical problem in computer science, and forms the basis of the current best-performing reference-based compression schemes for genome resequencing data. First, we present a new algorithm for the LCS problem. Then, we introduce an LCS-motivated reference-based compression scheme using the components of the LCS, rather than the LCS itself. For the...
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