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检索条件"任意字段=IEEE Computational Systems Bioinformatics Conference"

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Some challenges in computational biology

Some challenges in computational biology

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Asian Control conference

作者： M. Vidyasagar Advanced Technology Centre Tata Consultancy Services Limited Hyderabad India

Recent advances in experimental techniques in biology have resulted in a tremendous explosion in the amount of "raw data" available to the life sciences community. The challenge of computational biology is to turn this "raw data" into "information." In this paper, we review some of the many challenging problems in computational biology that are amenable to treatment using a systems approach. Though computational methods have a role to play in practically all aspects of the drug discovery process, attention is restricted here to just two areas, namely: genomics and proteomics. The list of references contains citations of sources of other problems to which the systems approach could be applied.

关键词： computational biology Genomics bioinformatics Biology computing Costs Databases Humans Drugs Proteins Very large scale integration

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Domain specific languages for cellular interactions

Domain specific languages for cellular interactions

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Annual International conference of the ieee Engineering in Medicine and Biology Society (EMBC)

作者： W.L. Harrison R.W. Harrison Department of Computer Science University of Missouri Columbia Columbia MO USA Departments of Computer Science & Biology Georgia State University Atlanta GA USA

bioinformatics is the application of computer science techniques to problems in biology, and this paper explores one such application with great potential: the modeling of life cycles of autonomous, intercommunicating cellular systems using domain-specific programming languages (DSLs). We illustrate this approach for the simple photo-synthetic bacterium R. Sphaeroides with a DSL called CellSys embedded in the programming language Haskell.

关键词： Domain specific languages Application software Computer languages DSL bioinformatics Computer science Cells (biology) systems biology computational biology Biological system modeling

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Spaghetti code, soupy logic, and the expression of genes

Spaghetti code, soupy logic, and the expression of genes

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Proceedings of the ieee computational systems bioinformatics conference, CSB

作者： J. Kent Baskin School of Engineering University of California Santa Cruz USA

The human genome could be characterized as 3 billion bases of the most convoluted spaghetti code in existence. While for the most part the genome is not something we engineers would want to emulate in our own products, there are some lessons to be learned from it. More importantly understanding the genome in all it's warts, convolutions, and spots of brilliance will lead to medical advances as fundamental as the understanding of infectious disease. Of peculiar interest to many of us who straddle the disciplines of software and biology is the study of gene expression. How does a cell decide which of its 25,000 genes to use at any given time? There are multiple regulatory networks which decide the usage patterns of a gene. The most fundamental of these networks - the interaction between transcription factor proteins and the DNA that they bind to - resembles in many ways a neural network implemented in soup. Studying and characterizing this soupy logic is by no means easy, but progress is being made on many fronts. Comparative genomics helps separate functional DNA from the relics of intracellular parasites and evolutionary dead ends that make up more than 90% of the human genome. Advances in mRNA sequencing have made it easier to locate the true transcription start site, which is a hot spot of regulatory activity. DNA microarrays allow us to measure in parallel the expression patterns of entire genomes. ChlP/Chip techniques can physically map the binding sites of transcription factors genome-wide. Developing software to evaluate, integrate, store, and display this data is a complex, but most worthwhile challenge. This talk will review some of the software developed both at UCSC and elsewhere to address this challenge.

关键词： Logic Genomics bioinformatics DNA Humans Biomedical engineering Convolutional codes Diseases Cells (biology) Gene expression

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Design and implementation of a computational grid for bioinformatics

Design and implementation of a computational grid for bioinf...

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ieee International conference on e-Technology, e-Commerce and e-Service

作者： Chao-Tung Yang Yu-Lun Kuo Chuan-Lin Lai High-Performance Computing Laboratory Department of Computer Science and Information Engineering Tunghai University Taichung Taiwan

ISBN: (纸本)0769520731

The popular technologies, Internet computing and grid technologies promise to change the way we tackle complex problems. They enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively transforms scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment and analysis. The FASTA is a tool for aligning multiple protein or nucleotide sequences. These two bioinformatics software, which we used is a distributed and parallel version. The software uses a message-passing library called MPI (message passing interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using globus toolkit (GT) and SUN grid engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented.

关键词： Grid computing bioinformatics Biology computing Sequences Large-scale systems Databases Internet Physics Proteins Software libraries

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A novel GA-based algorithm approach to fast biosequence alignment

A novel GA-based algorithm approach to fast biosequence alig...

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ieee conference on Cybernetics and Intelligent systems

作者： Ying-Tung Hsiao Cheng-Long Chuang Cheng-Chih Chien Department of Electrical Engineering Tamkang University Taipei Taiwan

ISBN: (纸本)0780386434

This paper presents a novel approach algorithm for bimolecular sequences alignment. Sequences comparison is the most important primitive operation in computational biology. There are many computational requirements for a alignment algorithm such as computer memory space requirement and computational complexity (computation time). To overcome the computational complexity of sequence alignment, the presented method first randomly divides the entire bimolecular sequences into several small sequences, and search for a partial near optima solution. After all of the partial near optima searching operations arc completed, the algorithm starts to search for better global optima by scan the new bimolecular sequences that are combined from the optimized small sequences. It allows pairwise alignment in each small sequence and does not apply dynamic programming at any optimization operation. The proposed algorithm also provides highly alignment efficient and very fast performance. Moreover, the proposed algorithm has been implemented in an x86 program, and used to verify the validity of the proposed algorithm and experiment on real DNA and protein datasets.

关键词： Sequences DNA bioinformatics Biology computing computational biology computational complexity Dynamic programming Proteins Genomics Software tools

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Modeling complex cellular networks - robust switching in the cell cycle ensures a piecewise linear reduction of the regulatory network

Modeling complex cellular networks - robust switching in the...

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ieee conference on Decision and Control

作者： O. Eriksson Yishao Zhou J. Tegner Stockholm Bioinformatics Center Stockholm Sweden and the Division for Computational Biology Department of Physics Linköping University Linkoping Sweden Department of Mathematics Stockholm University Stockholm Sweden Division for Computational Biology Department of Physics Linköping University Linkoping Sweden Center for Genomics and Bioinformatics Karolinska Institute Stockholm Sweden

Cellular networks are inherently complex due to their large number of genes and proteins interacting through non-linear feedback loops. The identification of cellular networks from large-scale parallel measurements from the activity of genes and proteins is a tremendous challenge in the postgenomic era, i. e. after the sequencing of the genome. Traditionally, this system identification problem has been viewed as a huge parameter estimation problem of an unknown non-linear system. Here we develop an approach where we approximate the complex system equations with a piecewise linear system, using a computational model of the cell cycle as a proof of principle. The modular and sparse structure of the cellular network makes it possible, to divide the model into subsystems, each having only a small number of inputs and outputs. As a rule, the subsystems operate as switches with or without delay. Since the cell cycle, as most biological systems, is robust against perturbations, the subsystems can be replaced by step functions and the main dynamical behaviour of the full complex cellular network can therefore be captured by the piecewise linear system. If other cellular networks are robust, sparse and modular, our approach of targeting a reduced system description instead of the full complex system, set the stage for not only a thorough characterization of the system dynamics but most importantly, it reduces the complexity of the parameter estimation problem.

关键词： Land mobile radio cellular systems Robustness Piecewise linear techniques Proteins Parameter estimation Feedback loop Large-scale systems Genomics bioinformatics System identification

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3D structural homology detection via NMR resonance assignment

3D structural homology detection via NMR resonance assignmen...

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Proceedings of the ieee computational systems bioinformatics conference, CSB

作者： C.J. Langmead B.R. Donald Department of Computer Science Carnegie Mellon University Pittsburgh PA USA Chemistry Department Dartmouth College Hanover NH USA

One goal of the structural genomics initiative is the identification of new protein folds. Sequence-based structural homology prediction methods are an important means for prioritizing unknown proteins for structure determination. However, an important challenge remains: two highly dissimilar sequences can have similar folds - how can we detect this rapidly, in the context of structural genomics? High-throughput NMR experiments, coupled with novel algorithms for data analysis, can address this challenge. We report an automated procedure, called HD, for detecting 3D structural homologies from sparse, unassigned protein NMR data. Our method identifies 3D models in a protein structural database whose geometries best fit the unassigned experimental NMR data. HD does not use, and is thus not limited by sequence homology. The method can also be used to confirm or refute structural predictions made by other techniques such as protein threading or homology modelling. The algorithm runs in O(pn + pn/sup 5/2/ log (cn) + p log p) time, where p is the number of proteins in the database, n is the number of residues in the target protein and c is the maximum edge weight in an integer-weighted bipartite graph. Our experiments on real NMR data from 3 different proteins against a database of 4,500 representative folds demonstrate that the method identifies closely related protein folds, including sub-domains of larger proteins, with as little as 10-30% sequence homology between the target protein (or sub-domain) and the computed model. In particular, we report no false-negatives or false-positives despite significant percentages of missing experimental data.

关键词： Nuclear magnetic resonance Proteins Genomics bioinformatics High definition video Prediction methods Data analysis Solid modeling Spatial databases Geometry

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Optimization of *** heat shock response parameter tuning using distributed and integrated genetic algorithms

Optimization of *** heat shock response parameter tuning usi...

引用

ieee International conference on systems, Man and Cybernetics

作者： S. Tanaka H. Kurata T. Ohashi Kyushu Institute of Technology Fukuoka Japan Department of Bioscience and Bioinformatics Kyushu Institute of Technology Fukuoka Japan

The progress of computer made the analysis that was difficult in traditional technology possible. In gene regulatory network simulation to recreate and understand actual biological reaction, we build a reaction model and find the several unknown parameters in order to show the same behavior as actual. However it is difficult to optimize them because the scopes of them are logarithm scale wide and the fitness space is multidimensional and multimodal. We optimized it using distributed genetic algorithms (DGA) which has multiple populations. DGA showed better performance, if and only if the parameter of the emigrating operation is appropriate. Therefore we propose distributed and integrated genetic algorithms (DIGA) to reduce the cost to find the appropriate parameters of operation. We carried out some optimizing experiments on parameter tuning of heat shock response simulation of *** and several mathematical functions and inspected the characteristic of DIGA.

关键词： Electric shock Genetic algorithms Biological system modeling computational modeling Dissolved gas analysis Cities and towns Biology computing bioinformatics Distributed computing Algorithm design and analysis

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Deriving a novel codon index by combining period-3 and fractal features of DNA sequences

Deriving a novel codon index by combining period-3 and fract...

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Proceedings of the ieee computational systems bioinformatics conference, CSB

作者： Yan Qi Jianbo Gao Yinhe Cao Wen-wen Tung Department of Biomedical Engineering Johns Hopkins University Baltimore MD USA Department of Electrical and Computer Engineering University of Florida Gainesville FL USA National Center for Atmospheric Research Boulder CO USA

Summary form only given. When a gene finding algorithm incorporates multiple useful and non-redundant sources of information about coding regions, it becomes more successful. It is thus highly desirable to find new and efficient codon indices. Here we propose a novel codon index, which we call the period-3 fractal deviation (PFD). This is obtained by simultaneously considering two incompatible features of DNA sequences, the period-3 feature in coding regions and the fractal feature in both coding and non-coding regions. These two features are incompatible because period-3 defines a specific scale of three nucleotide bases while fractal means there are not any specific scales. The PFD is very different for coding and non-coding sequences, and is reading-frame-dependent. The accuracy of the PFD is evaluated by studying all of the 16 yeast chromosomes. It is found that the percentage accuracy is very high and quite independent of the sliding window size. It is also found that this percentage accuracy is much higher than when period-3 and fractal features are characterized alone, especially when the window size is small. This highly suggests that the method is not only useful for the study of long genome sequences, but may also be very powerful for the study of short DNA segments. The PFD is complementary to other codon indices, including Fourier measures of period-3. This makes it possible to integrate PFD with other measures. Indeed, integration of the PFD measure with those indices using the Fisher linear discriminant analysis significantly improves the accuracy of protein coding sequence identification; This implies the measure proposed here may be readily incorporated into existing gene finding algorithms. Other salient features of the method is that it is non-parametric, does not require training, and can be fully automated.

关键词： Fractals DNA Sequences Phase frequency detector Information resources Fungi Biological cells Genomics bioinformatics Linear discriminant analysis

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An investigation into computational methods for understanding gene regulation

An investigation into computational methods for understandin...

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ieee International conference on systems, Man and Cybernetics

作者： D. Manley P. Smith School of Computing Dublin Institute of Technology Ireland School of Computing and Technology University of Sunderland UK

This paper presents an analysis of the biological plausibility of utilising Boolean networks for modelling genetic networks. A number of Boolean network models currently exist which can mimic the development of organisms from their origin (i.e. fertilisation) to the fully formed species (e.g. human adult). They can also be used to model the development of certain pathological genetic conditions (e.g. cancer). In addition the paper reviews the first steps in the construction of Boolean networks that mimic real genetic networks. The papers proposes that while synchronous deterministic networks are the classical approach asynchronous or semi-synchronous updating mechanisms could prove to be a more viable alternative for modelling the development of organisms and important pathological conditions (such as cancer).

关键词： Biological system modeling Genetics Computer networks Organisms Genomics bioinformatics Boolean functions Biology computing Humans Pathology

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