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检索条件"任意字段=Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004"

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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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Separation of ion types in tandem mass spectrometry data interpretation - a graph-theoretic approach

Separation of ion types in tandem mass spectrometry data int...

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proceedings of the ieee computational systems bioinformatics conference, csb

作者： Bo Yan Chongle Pan V.N. Olman R.L. Hettich Ying Xu Department of Biochemical and Molecular Biology University of Georgia GA USA Genome Science and Technology Graduate School University of Tennessee TN USA Chemical Sciences Division Oak Ridge National Laboratory TN USA

Mass spectrometry is one of the most popular analytical techniques for identification of individual proteins in a protein mixture, one of the basic problems in proteomics. It identifies a protein through identifying its unique mass spectral pattern. While the problem is theoretically solvable, it remains a challenging problem computationally. One of the key challenges comes from the difficulty in distinguishing the N- and C-terminus ions, mostly b- and y-ions respectively. In this paper, we present a graph algorithm for solving the problem of separating b- from y-ions in a set of mass spectra. We represent each spectral peak as a node and consider two types of edges: a type-1 edge connects two peaks possibly of the same ion types and a type-2 edge connects two peaks possibly of different ion types, predicted based on local information. The ion-separation problem is then formulated and solved as a graph partition problem, which is to partition the graph into three subgraphs, namely b-, y-ions and others respectively, so to maximize the total weight of type-1 edges while minimizing the total weight of type-2 edges within each subgraph. We have developed a dynamic programming algorithm for rigorously solving this graph partition problem and implemented it as a computer program PRIME. We have tested PRIME on 18 data sets of high accurate FT-ICR tandem mass spectra and found that it achieved /spl sim/90% accuracy for separation of b- and y-ions.

关键词： Mass spectroscopy Peptides Databases bioinformatics Proteomics Protein sequence computational biology Chemical technology Genomics Sequences

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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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bioinformatics and computational systems biology: At the cross roads of biology, engineering and computation

Bioinformatics and computational systems biology: At the cro...

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26th Annual International conference of the ieee-Engineering-in-Medicine-and-Biology-Society

作者： Subramaniam, S Univ Calif San Diego La Jolla CA 92093 USA

ISBN: (纸本)0780384393

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.

关键词： computational systems biology bioinformatics Roads Biology computing Biological system modeling Object oriented modeling computational biology Data analysis systems biology Sequences

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Algorithms for estimating information distance with application to bioinformatics and linguistics

Algorithms for estimating information distance with applicat...

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Canadian conference on Electrical and Computer Engineering;Technology Driving Innovation, 2004

作者： Kaltchenko, Alexei Department of Physics Wilfrid Laurier University Waterloo Ont. N2L3C5 Canada

ISBN: (纸本)0780382536

We review unnormalized and normalized information distances based on incomputable notions of Kolmogorov complexity and discuss how Kolmogorov complexity can be approximated by data compression algorithms. We argue that optimal algorithms for data compression with side information can be successfully used to approximate the normalized distance. Next, we discuss an alternative information distance, which is based on relative entropy rate (also known as Kullback-Leibler divergence), and compression-based algorithms for its estimation. We conjecture that in bioinformatics and computational Linguistics this alternative distance is more relevant and important than the ones based on Kolmogorov complexity.

关键词： computational complexity

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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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GBTK: A toolkit for grid implementation of BLAST

GBTK: A toolkit for grid implementation of BLAST

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proceedings - Seventh International conference on High Performance Computing and Grid in Asia Pacific Region, HPCAsia 2004

作者： Kumar, Satish M. Joshi, Rajendra R. Bioinformatics Team Sci. and Engineering Computing Group Ctr. for Devmt. of Adv. Computing Pune India

ISBN: (纸本)076952138X

We describe the implementation of GBTK (Grid BLAST Tool Kit), a lightweight application specific grid framework for BLAST, for geographically distributed High Performance Computing (HPC) systems. This framework was built on the concept of synchronized web services using RPC (Remote Procedure Calls) encoded as XML (extensible Markup Language).

关键词： Distributed computer systems

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ieee/ACM SC 2004 conference, proceedings

IEEE/ACM SC 2004 Conference, Proceedings

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ieee/ACM SC2004 conference - Bridging Communities

ISBN: (纸本)0769521533

The proceedings contain 59 papers from the ieee/ACM SC 2004 conference, proceedings. The topics discussed include: using hardware counters to automatically improve memory performance;RPC-V: toward fault-tolerant RPC for internet connected desktop grids with volatile nodes;ultrascalable implicit finite element analyses in solid mechanics with over a half a billion degrees of freedom;advanced computational fluid dynamics simulations of projectiles with flow control;VIRACOCHA: an efficient parallelization framework for large-scale CFD post-processing in virtual environments;and analysis and modeling of advanced PIM architecture design tradeoffs.

关键词： Computer systems

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The simulated annealing method applied to protein structure prediction

The simulated annealing method applied to protein structure ...

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proceedings of 2004 International conference on Machine Learning and Cybernetics

作者： Chen, Wei-Feng Li, Kai-Yang Liu, Juan Laboratory of Biophysics Department of Physics Wuhan University Wuhan 430072 China Laboratory of Bioinformatics Department of Computer Science Wuhan University Wuhan 430072 China

ISBN: (纸本)0780384032

In this article, the united-residue energy function put forward by Harold A. Scheraga and contained multi-body interactions was described detailedly. Based on the molecular modeling, the simulated annealing method was applied to the conformation space searching, and following this dynamic formation and breaking of disulfide bonds were brought forward.

关键词： Proteins

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Methods of computational intelligence

Methods of computational intelligence

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2004 ieee International conference on Industrial Technology, ICIT

作者： Wilamowski, Bogdan M. IEEE Auburn University United States

Comparison of various methods of computational intelligence are presented and illustrated with examples. These methods include neural networks, fuzzy systems, and evolutionary computation. The presentation is focused on neural networks, their learning algorithms and special architectures. General learning rule as a function of the incoming signals is discussed. Other learning rules such as Hebbian learning, perceptron learning, LMS - Least Mean Square learning, delta learning, WTA - Winner Take All learning, and PCA - Principal Component Analysis are presented as a derivation of the general learning rule. Architecture specific learning algorithms for cascade correlation networks, Sarajedini and Hecht-Nielsen networks, functional link networks, polynomial networks, counterpropagation networks, RBF-Radial Basis Function networks are described. © 2004 ieee.

关键词： Artificial intelligence

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