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ieee International conference on bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Blayney, Jaine Haberland, Valeriia Lightbody, Gaye Browne, Fiona Queens Univ Belfast Sch Med Dent & Biomed Sci Belfast BT7 1NN Antrim North Ireland Univ London Tungsten Ctr Intelligent Data Analyt London WC1E 7HU England Univ Ulster Sch Comp & Math Coleraine BT52 1SA Londonderry North Ireland

ISBN: (纸本)9781467367981

The analysis of biological markers (biomarkers) have the ability to improve clinical outcomes of a disease through prediction and early detection. The constant improvement of next generation sequencing (NGS) technologies coupled with falling equipment price are driving research and application especially in the medical domain. NGS technology is being applied to cancer research promising greater understanding of carcinogenesis. However, as sequence capacity grows, algorithmic speed is becoming an important bottleneck. To understand these challenges we present a review on difficulties currently faced in discovering biomarkers. The review places the spotlight on sequencing technologies and the bottlenecks encountered in these pipelines. Cloud computing and high performance computing technologies such as Grid are summarized in tackling computational challenges presented by technologies and algorithms used in biomarker research.

关键词： bioinformatics Decision support systems Genomics Robustness Sequential analysis

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ieee BIBM 2016 Special Issue

IEEE TRANSACTIONS ON NANOBIOSCIENCE

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ieee TRANSACTIONS ON NANOBIOSCIENCE 2017年第5期16卷 312-313页

作者： Hu, Xiaohua Tony Drexel Univ Philadelphia PA 19104 USA Nortel Res Ctr Brampton ON Canada Verizon Lab Waltham MA USA DMW Software Silicon Valley CA USA Coll Comp & Informat Data Min & Bioinformat Lab Philadelphia PA 19104 USA NSF Ctr I U CRC Visual & Decis Informat NSF CVDI Philadelphia PA 19104 USA

bioinformatics and biomedicine research is fundamental to our understanding of complex biological systems, impacting the science and technology of fields ranging from agricultural and environmental sciences to pharmaceutical and medical sciences. This type of research requires close collaboration among multidisciplinary teams of researchers in computer science, statistics, physics, engineering, life sciences and medical sciences, and their interfaces. The ieee International conference on bioinformatics and Biomedicine aims to provide an open and interactive forum to catalyze the cross-fertilization of ideas from these disciplines and to bridge our knowledge gaps.

关键词： Special issues and sections Meetings bioinformatics computational systems biology Drugs

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Comparison and Evaluation of Signal Representations for a Carbon Nanotube computational Device

Comparison and Evaluation of Signal Representations for a Ca...

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ieee International conference on Evolvable systems (ICES)

作者： Lykkebo, Odd Rune Tufte, Gunnar Norwegian Univ Sci & Technol Dept Comp & Informat Sci N-7491 Trondheim Norway

ISBN: (纸本)9781479944798

Evolution in Materio (ElM) exploits properties of physical systems for computation. Evolution manipulates physical processes by stimulating materials by applying some sort of configuration signal. For materials such as liquid crystal and carbon nanotubes the properties of configuration data is rather open. In this work we investigate what kind of configuration data that most likely will be favourable for a carbon nanotube based device. An experimental approach targeting graph colouring is used to test three different types of signal representation: static voltages, square waves and a mixed signal representation. The results show that all signal representation was capable of producing a working device. In the experiments square wave representation produced the best result.

关键词： carbon nanotubes graph colouring liquid crystal devices mixed analogue-digital integrated circuits C EIM carbon nanotube computational device configuration data configuration signal evolution in materio liquid crystal material stimulation mixed signal representation physical computation systems physical process signal representations square wave representation static voltages bioinformatics Genomics colored graph signal representation Mixed analog digital integrated circuits Carbon Nanotubes enterprise instant messaging Epilepsy, Myoclonic, Infantile Physical Processes LIQUID CRYSTAL DISPLAY Liquid Crystals bioinformatics Genomics

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bioinformatics-inspired non-parametric modelling of pharmacokinetics-pharmacodynamics systems using differential neural networks

Bioinformatics-inspired non-parametric modelling of pharmaco...

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International Joint conference on Neural Networks (IJCNN) held as part of the ieee World Congress on computational Intelligence (ieee WCCI)

作者： Alfaro-Ponce, Mariel Chairez, Isaac Tecnol Monterrey Sch Engn & Sci Monterrey Mexico Inst Politecn Nacl Unidad Profes Interdisciplinaria Biotecnol Mexico City DF Mexico

ISBN: (纸本)9781728169262

Bionformatics and pharmacokinetics-pharmacodynamics (PKPD) systems are two conjugated tools to intensively explore the effect of new drugs on the human body running in-silico analysis. Usually, PKPD models do not consider all the biological reactions that explain the pharmaceutical effect. A complementary non-parametric modeling can be useful to recover the PKPD dynamics despite the uncertainties and external perturbations effect, which can reduce the degree of uncertainties on the drug evaluation. The aim of this study is to get a feasible non-parametric model of PKPD models using a bioinformatics inspired evaluation of antibacterial drug doses. A class of bioinformatics inspired differential neural networks (DNNs) responding to the dose modification provides the non-parametric approximation of the PKPD dynamics. The DNN modeling strategy was applied to approximate the dynamics of PKPD models under four different dosing regimes. The modeling strategy estimated the bacteria survival (measured as the logarithm of the colony forming units per milliliter) after the drug application. The same adjusted DNN-based model confirmed the ability of designing an off-line lab for evaluating diverse dosing strategies of antibacterial pharmaceutical.

关键词： Pharmacokinetics

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Workshop: Opportunities and challenges of non-model ecoinformatics

Workshop: Opportunities and challenges of non-model ecoinfor...

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2012 ieee 2nd International conference on computational Advances in Bio and Medical Sciences, ICCABS 2012

作者： Emrich, Scott Department of Computer Science and Engineering University of Notre Dame Notre Dame IN United States

ISBN: (纸本)9781467313216

Ongoing improvements in sequencing technology allow even greater analysis of questions related to genome biology. We will overview several of the opportunities and challenges of newer generation sequencing applied to ecological questions. We also discuss arthropod-focused applications and resulting distributed systems resources available for decentralized bioinformatics analysis. © 2012 ieee.

关键词： bioinformatics

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Creating a protein ontology resource

Creating a protein ontology resource

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2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Sidhu, Amandeep S. Dillon, Tharam S. Chang, Elizabeth IEEE Faculty of Information Technology University of Technology Sydney Australia School of Information Systems Curtin University of Technology Perth Australia

ISBN: (纸本)0769524427

Protein Data Integration approaches at the moment considers data sources as data repositories, but not as applications;which in turn may embody complex interactions with other data sources. Current approaches do not provide methods both for generic mapping protein data representation, depicting interactions in data it describes and for interfacing existing data. The proposed Protein Ontology shows the value of hierarchy and relationships present in proteomics data. The creation of a Protein Ontology provides understanding of diverse types of data like: (1) Protein Entry Details, (2) 3D Structural Representations of Proteins, (3) Structural Folds and domains conserved in proteins, (4) Functional Domains and Families created based on Physiological and Pathological Functions of Proteins, and (5) Various Constraints like Genetic Defects and Chemical Properties of Cell that affect Final Stable Molecular Structure of Protein. Protein Ontology describes the concepts of interest in protein complex mechanisms and proteomics process. © 2005 ieee.

关键词： Proteins

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Towards Aggregation based I/O Optimization for Scaling bioinformatics Applications 44

Towards Aggregation based I/O Optimization for Scaling Bioin...

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44th Annual ieee-Computer-Society International conference on Computers, Software, and Applications (COMPSAC)

作者： Stratton, Jack Albert, Michael Jensen, Quentin Ismailov, Max Jagodzinski, Filip Islam, Tanzima Western Washington Univ Dept Comp Sci Bellingham WA 98225 USA Texas State Univ Dept Comp Sci San Marcos TX USA

ISBN: (纸本)9781728173030

bioinformatics software often integrates multiple off-the-shelf programs into a single compute pipeline. Each standalone program generates output, that is frequently saved into a plain-text file, which is then processed as input by the program that is responsible for the next stage of the computation. Modern advances in genome sequencing and protein structure resolution methods have yielded large amounts of data, that when processed by bioinformatics compute pipelines, results in vast numbers of file reads and writes. Since computation capabilities of large-scale distributed systems grow much faster than their I/O bandwidth, processing such big data using these compute pipelines will not scale as the amount of data grows. For this work, we motivate and demonstrate a dynamic interception-based I/O analysis tool to assess the file read and write characteristics of a protein mutation generation pipeline. We discuss how our analysis tool can be further extended to apply compression and in-site analysis and has the potential to scale UO-intensive bioinformatics applications on high performance computing (HPC) systems.

关键词： computational Biology high performance compute pipeline I/O aggregation

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Predictive Deep Network with Leveraging Clinical Measure as Auxiliary Task

Predictive Deep Network with Leveraging Clinical Measure as ...

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Biological Ontologies and Knowledge Bases Workshop at ieee International conference on bioinformatics and Biomedicine (ieee BIBM)

作者： Li, Xiangrui Zhu, Dongxiao Levy, Phillip Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Wayne State Univ Dept Emergency Med Detroit MI USA Wayne State Univ Cardiovasc Res Inst Detroit MI USA

ISBN: (纸本)9781509030507

Deep neural networks (DNNs) have made impressive improvements for predictive modeling in various fields. Successful network building for predictive tasks usually requires abundant data, for effectively learning high-level, non-additive information from raw input features. The merit of high-level learning makes DNN promising in clinical research, but the need for abundant data hampers DNN applications. To address this challenge, we propose the use of Auxiliary-Task-Augmented Network (ATAN), a predictive model (for primary target) with introducing auxiliary tasks as regularization. ATAN leverages clinically relevant measures as auxiliary targets and learns the clinical relevance explicitly. We apply ATAN in a clinical dataset of hypertension collected from a vulnerable demographic population (African-American) to demonstrate its effectiveness.

关键词： Predictive models Hypertension computational modeling Heart bioinformatics Electronic mail

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PoPS: A computational tool for modeling and predicting protease specificity

PoPS: A computational tool for modeling and predicting prote...

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Proceedings - 2004 ieee computational systems bioinformatics conference, CSB 2004

作者： Boyd, Sarah E. De La Banda, Maria Garcia Pike, Robert N. Whisstock, James C. Rudy, George B. Sch. of Comp. Sci. and Software Eng. Victorian Bioinformatics Consortium Monash University Melbourne Vic. 3800 Australia Department of Biochemistry Victorian Bioinformatics Consortium Monash University Melbourne Vic. 3800 Australia Genetics Division Walter/Eliza Hall Inst. Med. Res. 1G Royal Parade Parkville Vic. 3052 Australia

ISBN: (纸本)0769521940

Proteases play a fundamental role in the control of intra- and extracellular processes by binding and cleaving specific amino acid sequences. Identifying these targets is extremely challenging. Current computational attempts to predict cleavage sites are limited, representing these amino acid sequences as patterns or frequency matrices. Here we present PoPS, a publicly accessible bioinformatics tool (http://***/)which provides a novel method for building computational models of protease specificity that, while still being based on these amino acid sequences, can be built from any experimental data or expert knowledge available to the user. PoPS specificity models can be used to predict and rank likely cleavages within a single substrate, and within entire proteomes. Other factors, such as the secondary or tertiary structure of the substrate, can be used to screen unlikely sites. Furthermore, the tool also provides facilities to infer, compare and test models, and to store them in a publicly accessible database.

关键词： Computation theory

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Genome wide computational identification of regulatory RNAs in rice plant pathogen Xanthomonas oryzae

Genome wide computational identification of regulatory RNAs ...

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International conference on bioinformatics and systems Biology (BSB)

作者： Kumari, Priyanka Som, Anup Univ Allahabad Ctr Bioinformat Inst Interdisciplinary Studies Allahabad 211002 Uttar Pradesh India

ISBN: (纸本)9781538664346

Xanthomonas oryzae is a gram negative bacterial phytopathogen which causes leaf blight disease of rice plant, posing serious threat to the plants and their yield. Regulatory RNAs are heterogeneous functional RNA molecules which modulate/regulate gene expression, thus controlling a wide variety of physiological functions. As an effort to understand the role of regulatory RNAs in the physiology and pathogenesis of Xanthomonas oryzae, we identified candidate regulatory RNAs, such as riboswitches (Cobalamin, FMN, Glycine, SAM, TPP, crcB), small RNAs (asX1, asX3, asX4, sX2, sX5, sX6, sX7, sX9, sX11, sX12, sX13, sX14, Xoo1, Xoo2, Xoo5, Xoo8) and ribozyme (RNaseP_arch), using in silico approach. We also identified the genes regulated by these regulatory RNAs and their role.

关键词： Xanthomonas oryzae Regulatory RNAs:(II.) Ribozymes Riboswitches sRNA phytopathogen bioinformatics

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