The Experts below are selected from a list of 1806 Experts worldwide ranked by ideXlab platform
Peter J Thomas - One of the best experts on this subject based on the ideXlab platform.
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guest editorial biological applications of information theory in honor of Claude Shannon s centennial part ii
IEEE Transactions on Molecular Biological and Multi-Scale Communications, 2016Co-Authors: Alexander G Dimitrov, Faramarz Fekri, Aurel A Lazar, Stefan M Moser, Peter J ThomasAbstract:Claude Shannon, born on April 30, 1916, pioneered the mathematical theory of communication in his 1948 paper in the Bell System Technical Journal . Information theory has since provided the foundation for the digital revolution in communications technology. In addition, it has provided a powerful framework for investigating the fundamental limitations of naturally occurring communications, particularly in biological systems. This two-part special issue of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications honors Shannon’s centennial by highlighting recent progress in biological and bio-inspired information theory. Part I includes papers on applications of multivariate mutual information to data clustering, statistical thermodynamics of nonequilibrium chemical processes, information processing in neuronal systems, biochemical signal transduction systems, DNA sequencing, and the swarming of insects.
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guest editorial biological applications of information theory in honor of Claude Shannon s centennial part ii
IEEE Transactions on Molecular Biological and Multi-Scale Communications, 2016Co-Authors: Alexander G Dimitrov, Faramarz Fekri, Aurel A Lazar, Stefan M Moser, Peter J ThomasAbstract:Claude Shannon, born on April 30, 1916, pioneered the mathematical theory of communication in his 1948 paper in the Bell System Technical Journal . Information theory has since provided the foundation for the digital revolution in communications technology. In addition, it has provided a powerful framework for investigating the fundamental limitations of naturally occurring communications, particularly in biological systems. This two-part special issue of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications honors Shannon’s centennial by highlighting recent progress in biological and bio-inspired information theory. Part I includes papers on applications of multivariate mutual information to data clustering, statistical thermodynamics of nonequilibrium chemical processes, information processing in neuronal systems, biochemical signal transduction systems, DNA sequencing, and the swarming of insects.
Alexander G Dimitrov - One of the best experts on this subject based on the ideXlab platform.
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guest editorial biological applications of information theory in honor of Claude Shannon s centennial part ii
IEEE Transactions on Molecular Biological and Multi-Scale Communications, 2016Co-Authors: Alexander G Dimitrov, Faramarz Fekri, Aurel A Lazar, Stefan M Moser, Peter J ThomasAbstract:Claude Shannon, born on April 30, 1916, pioneered the mathematical theory of communication in his 1948 paper in the Bell System Technical Journal . Information theory has since provided the foundation for the digital revolution in communications technology. In addition, it has provided a powerful framework for investigating the fundamental limitations of naturally occurring communications, particularly in biological systems. This two-part special issue of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications honors Shannon’s centennial by highlighting recent progress in biological and bio-inspired information theory. Part I includes papers on applications of multivariate mutual information to data clustering, statistical thermodynamics of nonequilibrium chemical processes, information processing in neuronal systems, biochemical signal transduction systems, DNA sequencing, and the swarming of insects.
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guest editorial biological applications of information theory in honor of Claude Shannon s centennial part ii
IEEE Transactions on Molecular Biological and Multi-Scale Communications, 2016Co-Authors: Alexander G Dimitrov, Faramarz Fekri, Aurel A Lazar, Stefan M Moser, Peter J ThomasAbstract:Claude Shannon, born on April 30, 1916, pioneered the mathematical theory of communication in his 1948 paper in the Bell System Technical Journal . Information theory has since provided the foundation for the digital revolution in communications technology. In addition, it has provided a powerful framework for investigating the fundamental limitations of naturally occurring communications, particularly in biological systems. This two-part special issue of the IEEE Transactions on Molecular, Biological, and Multi-Scale Communications honors Shannon’s centennial by highlighting recent progress in biological and bio-inspired information theory. Part I includes papers on applications of multivariate mutual information to data clustering, statistical thermodynamics of nonequilibrium chemical processes, information processing in neuronal systems, biochemical signal transduction systems, DNA sequencing, and the swarming of insects.
R E Kahn - One of the best experts on this subject based on the ideXlab platform.
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a tribute to Claude e Shannon 1916 2001 society news
IEEE Communications Magazine, 2001Co-Authors: R E KahnAbstract:A tribute to Claude Shannon is presented. It is followed by an obituary that appeared in The New York Times on February 27, 2001. It is reprinted here with permission.
Ali Masoudinejad - One of the best experts on this subject based on the ideXlab platform.
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information theory in systems biology part ii protein protein interaction and signaling networks
Seminars in Cell & Developmental Biology, 2016Co-Authors: Zaynab Mousavian, Jose Luis Diaz, Ali MasoudinejadAbstract:By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed.
Sergei Nekhai - One of the best experts on this subject based on the ideXlab platform.
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Information theory and signal processing methodology to identify nucleic acid-protein binding sequences in RNA-protein interactions
2019 53rd Annual Conference on Information Sciences and Systems (CISS), 2019Co-Authors: Harry Shaw, Deborah Preston, Yuri Obukhov, Nagarajan Pattabiraman, Tatiana Ammosova, Sergei NekhaiAbstract:RNA binding proteins are known to modulate an impressive array of cellular processes. Recent studies have focused on a variety of techniques to analyze RNA-protein (RBP) complex formation including NMR, X-ray crystallography, and mass spectrometry. To explore the factors that regulate RBP formation, we developed a computational method as a step prior to biochemical validation of RBP by mass spectrometry. Here we describe a methodology to predict the sequences involved in RNA-protein complex formation including transient interactions. The approach is based on an information entropy-based algorithm calibrated against known ΔG and binding probabilities for RNA nucleotides-amino acid residues. The method is then used to predict binding sites of specific RNA associated proteins identified by mass spectroscopy of RNA associated proteins. The estimates of specific nucleotide peptide interactions was based on the Gibbs free energy of nucleotide-peptide fragments in a given RBP complex, and a dynamic model that uses multiple binding sites within a nucleotide-peptide fragment to quantify the binding affinity of weak and transient RNA-protein interactions. A concept originally described by Claude Shannon is now being used to foster a new paradigm for assisting in the search for specific RNA-protein binding sites. In this paper we will detail the following information, in order: 1. An information-theoretic based approach to modelling RNA-protein interactions down to specific RNA-protein complex motifs based upon information entropy; 2. The theory applied to a calibration dataset of known RNA-protein interactions to predict the RNA-protein binding motifs; 3. A prediction of RNA-protein binding motifs on a set of co-immunoprecipitation assays.
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information theory and signal processing methodology to identify nucleic acid protein binding sequences in rna protein interactions
Conference on Information Sciences and Systems, 2019Co-Authors: Harry Shaw, Deborah Preston, Yuri Obukhov, Nagarajan Pattabiraman, Tatiana Ammosova, Sergei NekhaiAbstract:RNA binding proteins are known to modulate an impressive array of cellular processes. Recent studies have focused on a variety of techniques to analyze RNA-protein (RBP) complex formation including NMR, X-ray crystallography, and mass spectrometry. To explore the factors that regulate RBP formation, we developed a computational method as a step prior to biochemical validation of RBP by mass spectrometry. Here we describe a methodology to predict the sequences involved in RNA-protein complex formation including transient interactions. The approach is based on an information entropy-based algorithm calibrated against known $\Delta \mathrm {G}$ and binding probabilities for RNA nucleotides-amino acid residues. The method is then used to predict binding sites of specific RNA associated proteins identified by mass spectroscopy of RNA associated proteins. The estimates of specific nucleotide peptide interactions was based on the Gibbs free energy of nucleotide-peptide fragments in a given RBP complex, and a dynamic model that uses multiple binding sites within a nucleotide-peptide fragment to quantify the binding affinity of weak and transient RNA-protein interactions. A concept originally described by Claude Shannon is now being used to foster a new paradigm for assisting in the search for specific RNA-protein binding sites. In this paper we will detail the following information, in order: 1. An information-theoretic based approach to modelling RNA-protein interactions down to specific RNA-protein complex motifs based upon information entropy; 2. The theory applied to a calibration dataset of known RNA-protein interactions to predict the RNA-protein binding motifs; 3. A prediction of RNA-protein binding motifs on a set of co-immunoprecipitation assays.