Computational systems biology
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The conference program will consist of plenary lectures, symposia, workshops and invitedsessions of the latest significant findings and developments in all the major fields of biomedical engineering.Submitted papers will be peer reviewed. Accepted high quality papers will be presented in oral and postersessions, will appear in the Conference Proceedings and will be indexed in PubMed/MEDLINE
The world's premier EDA and semiconductor design conference and exhibition. DAC features over 60 sessions on design methodologies and EDA tool developments, keynotes, panels, plus the NEW User Track presentations. A diverse worldwide community representing more than 1,000 organizations attends each year, from system designers and architects, logic and circuit designers, validation engineers, CAD managers, senior managers and executives to researchers and academicians from leading universities.
The CDC is the premier conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.
The ACC is the annual conference of the American Automatic Control Council (AACC, the U.S. national member organization of the International Federation for Automatic Control (IFAC)). The ACC is internationally recognized as a premier scientific and engineering conference dedicated to the advancement of control theory and practice. The ACC brings together an international community of researchers and practitioners to discuss the latest findings in automatic control. The 2020 ACC technical program will
The 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2020) will be held in Metro Toronto Convention Centre (MTCC), Toronto, Ontario, Canada. SMC 2020 is the flagship conference of the IEEE Systems, Man, and Cybernetics Society. It provides an international forum for researchers and practitioners to report most recent innovations and developments, summarize state-of-the-art, and exchange ideas and advances in all aspects of systems science and engineering, human machine systems, and cybernetics. Advances in these fields have increasing importance in the creation of intelligent environments involving technologies interacting with humans to provide an enriching experience and thereby improve quality of life. Papers related to the conference theme are solicited, including theories, methodologies, and emerging applications. Contributions to theory and practice, including but not limited to the following technical areas, are invited.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...
The IEEE Reviews in Biomedical Engineering will review the state-of-the-art and trends in the emerging field of biomedical engineering. This includes scholarly works, ranging from historic and modern development in biomedical engineering to the life sciences and medicine enabled by technologies covered by the various IEEE societies.
Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.
Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...
The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2004
Summary form only given. We are witnessing the emergence of the "data rich" era in biology. The myriad data in biology ranging from sequence strings to complex phenotypic and disease-relevant data pose a huge challenge to modern biology. The standard paradigm in biology that deals with hypothesis to experimentation (low throughput data) to models is being gradually replaced by data ...
2009 IEEE International Conference on Bioinformatics and Biomedicine, 2009
Computational systems biology is largely driven by mathematical modeling and simulation of biochemical networks, via continuous deterministic methods or discrete event stochastic methods. Although, the deterministic methods are efficient in predicting the macroscopic behavior of a system, they are severely limited by their inability to represent the stochastic effects of random molecular fluctuations at lower concentration. In this work, we ...
2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW), 2010
Today's emerging architectures have higher levels of parallelism incorporated within a processor. They require efficient strategies to extract the performance they have to offer. In our work, we develop architecture-aware parallel strategies to perform various kinds of pairwise computations - pairwise genomic alignments, and scheduling large number of general pairwise computations with applications to computational systems biology and materials science. ...
2009 International Workshop on High Performance Computational Systems Biology, 2009
UK National Cancer Registration data indicates that some 35,000 people each year are diagnosed with colorectal cancer (cancer of the large bowel and rectum) and 16, 000 die from the disease. The Colon Cancer Genetics Group (CCGG) at the University of Edinburgh investigates the relationship between genetic markers and colorectal cancer by using a significant part (560,000 markers, 1000 cases, ...
2006 IEEE International Conference on Granular Computing, 2006
EMBC 2011-Program-Systems in Synthetic Biology (Part I)-Pamela A. Silver
EMBC 2011-Program-Systems in Synthetic Biology (Part I)-Bruce Tidor
IMS 2015: Smart Textile Computational Systems
EMBC 2011-Workshop- Biological Micro Electro Mechanical Systems (BioMEMS): Fundamentals and Applications-Utkan Demirci
EMBC 2011-Keynote Lecture-Engineering Drug Dosing in Dynamic Biological Systems - David J. Balaban
EMBC 2011-Keynote Lectures and Panel Discussion-PT I-Subra Suresh
A Conversation About Mind/Brain Research and AI Development: IEEE TechEthics Interview
EMBC 2011-Workshop- Biological Micro Electro Mechanical Systems (BioMEMS): Fundamentals and Applications-Ali Khademhosseini
Planning in Robotics and Beyond - ICRA 2020
EMBC 2011-Workshop- Biological Micro Electro Mechanical Systems (BioMEMS): Fundamentals and Applications-Mehmet R. Dokmeci
EMBC 2011-Workshop-Biological Micro Electro Mechanical Systems (BioMEMS): Fundamentals and Applications-Michelle Khine
IMS 2015 Keynote: The Century of Biology is Great for Engineering
Norbert Wiener in the 21st Century Conference Concept
EMBC 2012 Theme Speaker: Dr. James Bassingthwaighte
Q&A with Marilyn Wolf: IEEE Rebooting Computing Podcast, Episode 13
EMBC 2011-Keynote Lectures and Panel Discussion-PT IV-Discussion
EMBC 2011 - Course: Virtual Reality and Robotics in Neurorehabilitation-Sergei Adamovich, PhD
Mind/Brain Research and AI Development: How Do They Inform Each Other? - IEEE TechEthics Panel
History of Robotics and Automation: Ruzena Bajcsy
Summary form only given. We are witnessing the emergence of the "data rich" era in biology. The myriad data in biology ranging from sequence strings to complex phenotypic and disease-relevant data pose a huge challenge to modern biology. The standard paradigm in biology that deals with hypothesis to experimentation (low throughput data) to models is being gradually replaced by data to hypothesis to models and experimentation to more data and models. And unlike data in physical sciences, that in biological sciences is almost guaranteed to be highly heterogeneous and incomplete. In order to make significant advances in this data rich era, it is essential that there be robust data repositories that allow interoperable navigation, query and analysis across diverse data, and a plug-and-play tools environment that will facilitate seamless interplay of tools and data. Further, the integrated data will enable the reconstruction and modeling of biological systems. This talk with address several of the challenges posed by enormous need for scientific data integration and modeling in biology with specific exemplars and possible strategies. The issues addressed will include: architecture of data and knowledge repositories; flat, relational and object-oriented databases ; ontologies in biology; reduction and analysis of data; legacy knowledge integration with data and systems level modeling in biology.
Computational systems biology is largely driven by mathematical modeling and simulation of biochemical networks, via continuous deterministic methods or discrete event stochastic methods. Although, the deterministic methods are efficient in predicting the macroscopic behavior of a system, they are severely limited by their inability to represent the stochastic effects of random molecular fluctuations at lower concentration. In this work, we have presented a novel method for simulating biochemical networks based on a deterministic solution with a modification that permits the incorporation of stochastic effects. To demonstrate the feasibility of our approach, we have tested our method on two previously reported biochemical networks. The results, while staying true to their deterministic form, also reflect the stochastic effects of random fluctuations that are dominant as the system transitions into a lower concentration. This ability to adapt to a concentration gradient makes this method particularly attractive for systems biology based applications.
Today's emerging architectures have higher levels of parallelism incorporated within a processor. They require efficient strategies to extract the performance they have to offer. In our work, we develop architecture-aware parallel strategies to perform various kinds of pairwise computations - pairwise genomic alignments, and scheduling large number of general pairwise computations with applications to computational systems biology and materials science. We present our schemes in the context of the IBM Cell BE, an example of a heterogeneous multicore, but are nevertheless applicable to any similar architecture, as well as general multicores with our strategies being cache- aware.
UK National Cancer Registration data indicates that some 35,000 people each year are diagnosed with colorectal cancer (cancer of the large bowel and rectum) and 16, 000 die from the disease. The Colon Cancer Genetics Group (CCGG) at the University of Edinburgh investigates the relationship between genetic markers and colorectal cancer by using a significant part (560,000 markers, 1000 cases, 1000 controls) of the biggest genotypic data set for large bowel cancer. However, the analysis is virtually intractable for a PC- based researcher (theoretical runtime of 400 days; 3.3TB of memory and hard disk space). CCGG collaborated with EPCC, the super computing centre of the University of Edinburgh, to optimise and parallelise the analysis code. We achieved a runtime of approximately 5 hours on 512 processor cores on HECToR, the national supercomputer of the UK. The use of EPCC's skills and HPC resources has enabled CCGG to explore new territory for genetic marker analysis in colorectal cancer.
The Synechococcus WH8102 knowledge base (http://www.csbl.bmb.uga.edu/WH8J02) is a Web based relational database developed to facilitate computational effort to reconstruct regulatory pathways and serve as a gateway for biologist to access the data. It is the repertoire that integrates a variety of knowledge derived both from literature and computational prediction. Those data are organized in hierarchical fashion. The basic building blocks are functional annotation and structure prediction of individual molecule. Those data are then organized into clusters based on computationally predicted operon, regulon and molecular complexes. Finally all data are complied into pathways derived from combined efforts of literature mining and computational prediction. A number of tools have been developed to facilitate the data retrieval including a SQL query engineer and several viewers to browse genome, molecular complexes and pathways.
We present a tool for parallel enumerative LTL model-checking and reachability analysis. The tool brings model checking to high-powered multi-core systems, as well as high-performance clusters. Boasting pluggable modelling language framework, it is possible to leverage the available parallel algorithms for multiple problem domains, by using suitable input language.
Biological pathway mapping is an important problem in the post-genomic era. We now present a new algorithm for pathway mapping in microbes. The algorithm considers not only sequence similarity among the template and target genes, but also the operon structures in the target genome. We formulated the mapping problem as a graph finding problem, and solved it by an integer-programming (IP) method. The goal is to minimize a linear object function subject to six constraints, such that maximal sequence similarity among the template and target genes are achieved, and at the same time, a minimal number of operons are covered in the target genome. Compared to our previous minimal spanning tree (MST) algorithm, the IP method has the following advantages: i) It is much faster and thus can map larger pathway involving a much large set of genes. ii) The IP method looks into the details of genes in the operons, and consequently avoids the many-to-one mapping mistakes that sometimes occur in the MST algorithm. We have compiled a large pathway training set to optimize the parameters of the program, and tested it by mapping 16 complex pathways from BioCyc onto E.coli K12 genome and the results are very promising.
Receptor tyrokine kinases are critical regulators of signal transduction pathways mediating cellular homeostasis. Enhanced kinase activities via mutation and other genetic alternations have been observed in many human cancers. We performed a 4 ns molecular dynamics (MD) simulation of the kinase domain of fibroblast growth factor receptor 1 (FGFRl) to study the mechanism that controls its activation. Our simulation revealed the key atomic events that allow substrate access and kinase activation. This dynamic information will facilitate the design of new inhibitors for use in the treatment of cancer.
Coupling computational modeling and information processing in biology and medicine is a major challenge for better comprehending structures and functions of living systems. Signal processing should extract the relevant information required to explore complex organization levels, at all space and time scales. Advances coming from applied physics and mathematics are challenged by extremely hot topics in biology and medicine. The biomedical scene has proven to be the most difficult to address due to the fact that biomedical processes involve nonGaussian, nonlinear, and nonstationary components. This paper provides some clues on processing schemes such as time and frequency transforms, blind signal separation, independent component analysis, empirical mode decomposition, particle methods and Kernel methods that may help in lessening the ambiguity about the observed components of the mixtures to be handled and, this way, facilitating their matching with models.
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