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

共 878 条记录，以下是151-160 订阅

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17α-Ethinylestradiol Analysis of Endo- and Exometabolome of Ulva lactuca (Chlorophyta) by ¹H-NMR Spectroscopy and bioinformatics Tools 12th

17α-Ethinylestradiol Analysis of Endo- and Exometabolome of...

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12th International conference on Practical Applications of computational Biology and bioinformatics (PACBB)

作者： Cabral, Debora Cardoso, Sara Rocco, Silvana Sforca, Mauricio Hengeltraub, Simone Fanan Bauer, Claudia Rocha, Miguel Maraschin, Marcelo Univ Fed Santa Catarina Plant Morphogenesis & Biochem Lab Florianopolis SC Brazil Univ Minho Ctr Biol Engn Braga Portugal Brazilian Biosci Natl Lab LNBio CNPEM Campinas SP Brazil

ISBN: (纸本)9783319987026;9783319987019

The uptake of 17 alpha-ethinylestradiol (EE2) by the green alga Ulva lactuca and its effects on the metabolome of that macroalgae have been investigated using H-1-NMR spectroscopy. To this end, U. lactuca in vitro cultures have been acutely (48 h) exposed to the estrogen and both, endo-and exometabolome were investigated. Bioinformatic analyses were performed to integrate and analyze endo-and exometabolic profiles allowing the detection of EE2 into exometabolome samples and identifying very important parameters (VIPs), i.e., H-1-NMR resonances, responsible for grouping similar U. lactuca metabolic profiles and biochemical phenotypes.

关键词： Ulva lactuca 17 alpha-ethinylestradiol NMR spectroscopy Endometabolome Exometabolome

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Solving subset sum problem using EN P system with active membranes 8

Solving subset sum problem using EN P system with active mem...

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Joint 8th International conference on Soft Computing and Intelligent systems (SCIS) / 17th International Symposium on Advanced Intelligent systems (ISIS)

作者： Shiiba, Tomohiro Fujiwara, Akihiro Kyushu Inst Technol Grad Sch Comp Sci & Syst Engn Iizuka Fukuoka 8208502 Japan

ISBN: (纸本)9781509026784

Membrane computing, which is a computational model inspired by the structures and behaviors of living cells, has considerable attention as one of non-silicon based computing. As a derived model of the membrane computing, a numerical P system has been proposed from structures of living cells and economics. The numerical P system contains a number of numerical variables, which are evolved according to programs. An enzymatic numerical P system (EN P system) is also a variant of P systems such that a number of variables, which are called enzymes, are used to promote evolution programs. In the present paper, we first define membrane division on the EN P system. Then, we propose an EN P system with active membranes for solving the subset sum problem. We show that the EN P system works in O(n) parallel steps and O(n2(n)) sequential steps.

关键词： bioinformatics

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Generalized Nets as Tools for Modelling of the Neural Networks 10

Generalized Nets as Tools for Modelling of the Neural Networ...

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10th ieee International conference on Intelligent systems, IS 2020

作者： Atanassov, Krassimir Sotirov, Sotir Asen Zlatarov University Prof. Yakimov 1 bul. Burgas Bulgaria Bioinformatics and Mathematical Modelling Department Institute of Biophysics and Biomedical Engineering Bulgarian Academy of Sciences Acad. G. Bonchev Str. Block 105 Sofia1113 Bulgaria

ISBN: (数字)9781728154565

ISBN: (纸本)9781728154565

In a series of papers, Generalized Nets (GNs) are constructed representing the functioning and the results of the work of different types of Neural Networks (NNs). In the present research, we show that the functioning and the results of the work of a given NN can be represented by a GN from a very simple type, but the so constructed GN-model can be used for extension of the concept of NNs. © 2020 ieee.

关键词： Artificial neural networks Biological neural networks Multi-layer neural network Mathematical model Biological system modeling Indexes

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Transmission network expansion planning with a hybrid meta-heuristic method of parallel tabu search and ordinal optimization

Transmission network expansion planning with a hybrid meta-h...

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2007 International conference on Intelligent systems Applications to Power systems, ISAP

作者： Mori, Hiroyuki Iimura, Yoshinori IEEE Dept. of Electronics and Bioinformatics Meiji University 1-1-1 Higashimita Tama-ku Kawasaki 214-8571 Japan

ISBN: (纸本)9860130868

This paper proposes a hybrid meta-heuristic method of parallel tabu search (PTS) and ordinal optimization (OO) for transmission network expansion planning in power systems. It determines the optimal structure that keeps the balance between generations and loads. The formulation is expressed as a combinatorial optimization problem that is very hard to solve. PTS is one of meta-heuristics that is useful for solving a combinatorial optimization. To speed up computational time of PTS, OO is used to reduce the number of solution candidates in a probabilistic way. The proposed method with OO-TS is successfully applied to a sample system.

关键词： Combinatorial optimization

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Evolutionary sequence divergence predicts protein sub-cellular localization signals

Evolutionary sequence divergence predicts protein sub-cellul...

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5th ieee International conference on systems Biology, ISB 2011

作者： Fukasawa, Yoshinori Leung, Ross K.K. Tsui, Stephen K.W. Horton, Paul Department of Computational Biology Graduate School of Frontier Sciences University of Tokyo Kashiwa Japan Hong Kong Bioinformatics Centre School of Biomedical Sciences Chinese University of Hong Kong Shatin Hong Kong Computational Biology Research Center Advanced Industrial Science and Technology Tokyo Japan

ISBN: (纸本)9781457716669

Protein sub-cellular localization is a central problem in understanding cell biology and has been the focus of intense research. In order to predict localization from amino acid sequence a myriad of features have been tried: including amino acid composition, sequence similarity, the presence of certain motifs or domains, and many others. Surprisingly, sequence conservation of sorting motifs has not yet been employed, despite its extensive use for tasks such as the prediction of transcription factor binding sites. Here, we flip the problem around, and present a proof of concept for the idea that the lack of sequence conservation can be a useful feature for localization prediction. © 2011 ieee.

关键词： Proteins

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Beyond Databases, Architectures, and Structures: 10th International conference, BDAS 2014, Ustron, Poland, May 27-30, 2014. Proceedings 1

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丛书名： Communications in Computer and Information Science 424

2014年

作者： Stanislaw Kozielski, Dariusz Mrozek, Pawel Kasprowski, Bożena Małysiak-Mrozek, Daniel Kostrzewa (eds.)

ISBN: (数字)9783319069326

ISBN: (纸本)9783319069319;9783319069326

This book constitutes the refereed proceedings of the 10th ieee International conference Beyond Databases, Architectures, and Structures, BDAS 2014, held in Ustron, Poland, in May 2014. This book consists of 56 carefully revised selected papers that are assigned to 11 thematic groups: query languages, transactions and query optimization; data warehousing and big data; ontologies and semantic web; computational intelligence and data mining; collective intelligence, scheduling, and parallel processing; bioinformatics and biological data analysis; image analysis and multimedia mining; security of database systems; spatial data analysis; applications of database systems; Web and XML in database systems.

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Aggregating Structural Features for computational Analysis of Mutations in BRCT Domains of BRCA1 Protein

Aggregating Structural Features for Computational Analysis o...

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2023 International conference on Informatics, Multimedia, Cyber and Information systems, ICIMCIS 2023

作者： Hidayat, Alam Ahmad Nirwantono, Rudi Isnan, Mahmud Trinugroho, Joko Pebrianto Pardamean, Bens Bina Nusantara University School of Computer Science Bioinformatics and Data Science Research Center Mathematics Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Bioinformatics and Data Science Research Center Biotechnology Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Binus Graduate Program Bioinformatics and Data Science Research Center Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350307306

Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein structural features of the protein mutations might be suitable in this case. In this work, we focus on BRCT domains of BRCA1 gene that is widely studied in breast cancer studies. We retrieved 88 selected missense variants found in BRCT domains annotated in both ClinVar and gnomAD databases. To computationally characterize the pathogenic property of the mutations we used two types of features extracted from protein structures: a change in free Gibbs energy and a set of features derived from molecular dynamics simulations of each mutant. Using a dimensional reduction and Gaussian mixture model (GMM)-based clustering we demonstrate that the variants are segregated into two regions that may correspond to their pathogenic status. This method can be a potential computational pipeline for providing the preliminary mechanistic interpretation of mutation effects in terms of their thermodynamic and structural features. © 2023 ieee.

关键词： Proteins

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A graph theoretic algorithm for removing redundant protein sequences

A graph theoretic algorithm for removing redundant protein s...

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3rd International conference on bioinformatics and Biomedical Engineering, iCBBE 2009

作者： Pengfei, Liu Zhenbing, Zeng Ziliang, Qian KaiYan, Feng Yudong, Cai Software Engineering Institute of East China Normal University 3663 North Zhongshan Road Shanghai 200062 China CAS-MPG Partner Institute for Computational Biology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences 320 Yueyang Road Shanghai 200031 China Bioinformatics Center Key Lab. of Systems Biology Shanghai Institutes for Biological Sciences 320 Yueyang Road Shanghai 200031 China Graduate School of the Chinese Academy of Sciences 19 Yuquan Road Beijing 100039 China Division of Imaging Science and Biomedical Engineering University of Manchester Stopford Building M13 9PT United Kingdom Institute of System Biology Shanghai University 99 ShangDa Road Shanghai 200244 China

ISBN: (纸本)9781424429028

Many biological sequence databases have redundant sequences which are not helpful to statistical analysis and require more computational time and resources to process. This lead us to design a new and fast program to generate a non-redundant sequence set. A graph theoretic algorithm was designed to process BLAST output and remove redundant proteins from a protein sequence database. We have developed a program named BlastCuller which can be used to generate a non-redundant protein database. BlastCuller is a flexible program with a parameter of sequence similarity cutoff, which can be a decimal from 0.0 to 1.0. This program can be downloaded from http://***/BlastCuller. html. ©2009 ieee.

关键词： Graph theory

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AI in bioinformatics and Genomics

AI in Bioinformatics and Genomics

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2024 International conference on Intelligent and Innovative Practices in Engineering and Management, IIPEM 2024

作者： Mukherjee, Sumita Thapliyal, Kavita Maurya, Alka Chaudhary, Naina Sudeshna, Sushree Amity University AIBS Noida India SIIB Pune India Amity University Tashkent Uzbekistan

ISBN: (纸本)9798350390049

Artificial intelligence (AI) has revolutionized various fields, including bioinformatics and genomics, by offering powerful tools and techniques to analyse and interpret complex biological data. This research paper explores the significant role of AI in bioinformatics and genomics, highlighting its applications, advancements, challenges, and future directions. Through a comprehensive review of relevant literature, case studies, and examples, and aims the power of AI transformation to provide insights on the study of biological systems, accelerating advancements in personalized medicine and biotechnology and enhancing our understanding of genomics. These areas have risen from the needs of biologists to utilize and help interpret the vast amounts of data that are constantly being gathered in genomic research. Artificial intelligence (AI) has increasingly gained attention in bioinformatics research and computational molecular biology has become common for the researchers to apply the off-shelf systems with the availability of different types of AI algorithms. At present researchers are facing difficulties in choosing the best method that could be applied to a specific data set, with various intelligent methods available in the literature. The researchers need to apply machine learning and AI with different tools and techniques which present the data in an annotated with context, estimates of accuracy, proper predictions and explanation. comprehensible fashion. This article aims to review the use of AI in the areas of bioinformatics and computational molecular biology (DNA sequencing). The AI in functional genomics, and its application in this paper defines the importance of applicability and interpretability including ethical, legal and economic issues. © 2024 ieee.

关键词： accelerating advancements AI bioinformatics biotechnology complex biological data Genomics

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HTSeq-Hadoop: Extending HTSeq for Massively Parallel Sequencing Data Analysis using Hadoop 10

HTSeq-Hadoop: Extending HTSeq for Massively Parallel Sequenc...

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10th ieee International conference on e-Science (e-Science)

作者： Siretskiy, Alexey Spjuth, Ola Uppsala Univ Dept Informat Technol SE-75105 Uppsala Sweden Uppsala Univ Dept Pharmaceut Biosci SE-75124 Uppsala Sweden Uppsala Univ Sci Life Lab SE-75124 Uppsala Sweden

ISBN: (纸本)9781479942879

Hadoop is a convenient framework in e-Science enabling scalable distributed data analysis. In molecular biology, next-generation sequencing produces vast amounts of data and requires flexible frameworks for constructing analysis pipelines. We extend the popular HTSeq package into the Hadoop realm by introducing massively parallel versions of short read quality assessment as well as functionality to count genes mapped by the short reads. We use the Hadoop-streaming library which allows the components to run in both Hadoop and regular Linux systems and evaluate their performance in two different execution environments: A single node on a computational cluster and a Hadoop cluster in a private cloud. We compare the implementations with Apache Pig showing improved runtime performance of our developed methods. We also inject the components in the graphical platform Cloudgene to simplify user interaction.

关键词： bioinformatics Hadoop Map-Reduce Massively Parallel Sequencing

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