Search Results - Computing Algorithms and Bioinformatics

Quantum algorithm for bioinformatics to compute the similarity between proteins

Authors: Anthony Chagneau Yousra Massaoudi Imene Derbali et al.

Source: IET Quantum Communication, Vol 5, Iss 4, Pp 417-442 (2024)

Subject Terms: graph theory, probability, quantum computing, random processes, Telecommunication, TK5101-6720

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Relation: https://doaj.org/toc/2632-8925

Access URL: https://doaj.org/article/e5f700c4a9c34aceb5001c62e9f6b9c0

Application of High-Throughput Computing in Bioinformatics

Authors: Swindells, Mark Rae, Mark Pearce, Martyn et al.

Source: Philosophical Transactions: Mathematical, Physical and Engineering Sciences, 2002 Jun . 360(1795), 1179-1189.

Access URL: https://www.jstor.org/stable/3066432

Online Tuning of PID Controllers Based on Membrane Neural Computing

Authors: Antonic, Nemanja Khalid, A. H. Hamila, M. E. et al.

Source: Lecture Notes on Data Engineering and Communications Technologies. :455-464

Subject Terms: Bioinformatics, Controllers, Electric control equipment, Membranes, Proportional control systems, Tuning, Engineering practices, Gain tuning, Membrane algorithm, Membrane computing, Neural computing, Neural membranes, Neural-networks, Online gain tuning, Online tuning, PID controllers, Three term control systems, Neural network, PID controller

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Access URL: https://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-61961

From Serial to Parallel: Enhancing Needleman-Wunsch Performance through GPU-Based Computing

Authors: Yustina Sri Suharini Wisnu Ananta Kusuma Sri Nurdiati et al.

Source: Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), Vol 9, Iss 5, Pp 1183-1192 (2025)

Subject Terms: global sequence alignment, gpu computing, needleman-wunsch algorithm, Systems engineering, TA168, Information technology, T58.5-58.64

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Relation: https://jurnal.iaii.or.id/index.php/RESTI/article/view/6620; https://doaj.org/toc/2580-0760

Access URL: https://doaj.org/article/62582c7417f246e7b42f8af4156b947f

Research on symptoms composition, time series evolution, and network visualisation of interstitial cystitis based on complex network community discovery algorithm

Authors: Lei Pang Zijun Ding Xiaodong Bian et al.

Source: IET Systems Biology, Vol 18, Iss 1, Pp 1-13 (2024)

Subject Terms: big data, bioinformatics, biology computing, combinatorial mathematics, complex networks, data analysis, Biology (General), QH301-705.5

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Relation: https://doaj.org/toc/1751-8849; https://doaj.org/toc/1751-8857

Access URL: https://doaj.org/article/ac21978869c640188a8a6b62fef7109b

Guest editors’ note: Special issue on novel high-performance computing algorithms and platforms in bioinformatics

Authors: José M. Cecilia

Source: The International Journal of High Performance Computing Applications. 34:3-4

Subject Terms: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://journals.sagepub.com/doi/full/10.1177/1094342019889705
https://journals.sagepub.com/doi/pdf/10.1177/1094342019889705
https://dblp.uni-trier.de/db/journals/ijhpca/ijhpca34.html#Cecilia20

Derivation and Analysis of Distributed Computing Algorithms in Biological Systems

Authors: Chandrasekhar, Arjun

Subject Terms: Bioinformatics, Computer science, Ecology, Algorithms in Nature, Ant Biology, Distributed Computing, Neuroscience, Optimization

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Access URL: https://escholarship.org/uc/item/03v7w5sf
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FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

Authors: Czajka, Jeffrey J Kim, Joonhoon Tang, Yinjie J et al.

Source: Bioinformatics. 41(9)

Subject Terms: 31 Biological Sciences (for-2020), 3106 Industrial Biotechnology (for-2020), Genetics (rcdc), Biotechnology (rcdc), Bioengineering (rcdc), Escherichia coli (mesh), Metabolic Engineering (mesh), Software (mesh), Synthetic Biology (mesh), Pseudomonas putida (mesh), Machine Learning (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Metabolic Networks and Pathways (mesh), Pseudomonas putida (mesh), Escherichia coli (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Software (mesh), Metabolic Networks and Pathways (mesh), Synthetic Biology (mesh), Metabolic Engineering (mesh), Machine Learning (mesh), Escherichia coli (mesh), Metabolic Engineering (mesh), Software (mesh), Synthetic Biology (mesh), Pseudomonas putida (mesh), Machine Learning (mesh), Genome, Bacterial (mesh), Algorithms (mesh), Metabolic Networks and Pathways (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)

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DNABERT-S: pioneering species differentiation with species-aware DNA embeddings

Authors: Zhou, Zhihan Wu, Weimin Ho, Harrison et al.

Source: Bioinformatics. 41(Supplement_1)

Subject Terms: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), 46 Information and Computing Sciences (for-2020), 4611 Machine Learning (for-2020), Human Genome (rcdc), Genetics (rcdc), Generic health relevance (hrcs-hc), 3 Good Health and Well Being (sdg), Sequence Analysis, DNA (mesh), DNA (mesh), Genomics (mesh), Algorithms (mesh), Species Specificity (mesh), Genome (mesh), 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3105 Genetics (for-2020), 4611 Machine Learning (for-2020), Human Genome (rcdc), Genetics (rcdc), Generic health relevance (hrcs-hc), 3 Good Health and Well Being (sdg), DNA (mesh), Sequence Analysis, DNA (mesh), Genomics (mesh), Species Specificity (mesh), Genome (mesh), Algorithms (mesh), Sequence Analysis, DNA (mesh), DNA (mesh), Genomics (mesh), Algorithms (mesh), Species Specificity (mesh), Genome (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)

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SetBERT: the deep learning platform for contextualized embeddings and explainable predictions from high-throughput sequencing

Authors: Ludwig, David W Guptil, Christopher Alexander, Nicholas R et al.

Source: Bioinformatics. 41(7)

Subject Terms: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Human Genome (rcdc), Genetics (rcdc), Machine Learning and Artificial Intelligence (rcdc), 3 Good Health and Well Being (sdg), Deep Learning (mesh), High-Throughput Nucleotide Sequencing (mesh), Sequence Analysis, DNA (mesh), Microbiota (mesh), Software (mesh), Computational Biology (mesh), Algorithms (mesh), Sequence Analysis, DNA (mesh), Computational Biology (mesh), Algorithms (mesh), Software (mesh), High-Throughput Nucleotide Sequencing (mesh), Microbiota (mesh), Deep Learning (mesh), Deep Learning (mesh), High-Throughput Nucleotide Sequencing (mesh), Sequence Analysis, DNA (mesh), Microbiota (mesh), Software (mesh), Computational Biology (mesh), Algorithms (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)

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Kingdom-wide CRISPR guide design with ALLEGRO

Authors: Mohseni, Amirsadra Nia, Reyhane Ghorbani Tafrishi, Aida et al.

Source: Nucleic Acids Research. 53(15)

Subject Terms: Biological Sciences, Bioinformatics and Computational Biology, Biotechnology, Genetics, Human Genome, Generic health relevance, RNA, Guide, CRISPR-Cas Systems, CRISPR-Cas Systems, Genome, Fungal, Gene Editing, Algorithms, Kluyveromyces, Saccharomyces cerevisiae, Clustered Regularly Interspaced Short Palindromic Repeats, Yarrowia, Rhodotorula, Gene Library, Saccharomycetales, Environmental Sciences, Information and Computing Sciences, Developmental Biology, Biological sciences, Chemical sciences, Environmental sciences

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TRFill: synergistic use of HiFi and Hi-C sequencing enables accurate assembly of tandem repeats for population-level analysis.

Authors: Wen, Huaming Yang, Jinbao Zhao, Xianjia et al.

Source: Genome biology. 26(1)

Subject Terms: Centromere, Telomere, Humans, Sequence Analysis, DNA, Tandem Repeat Sequences, Algorithms, Software, Solanum lycopersicum, Gap filling, Genome assembly, Reference-guided genome assembly, Segmental duplications, Tandem repeats, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics

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https://escholarship.org/content/qt1s4297xt/qt1s4297xt.pdf

clusterMaker2: a major update to clusterMaker, a multi-algorithm clustering app for Cytoscape

Authors: Utriainen, Maija Morris, John H

Source: BMC Bioinformatics. 24(1)

Subject Terms: Biological Sciences, Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Bioengineering, Generic health relevance, Mobile Applications, Saccharomyces cerevisiae, Algorithms, Protein Interaction Maps, Cluster Analysis, Clustering, Community detection, Network analysis, Visualization, Cytoscape, Mathematical Sciences, Information and Computing Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences

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Replacing non-biomedical concepts improves embedding of biomedical concepts

Authors: Niyonkuru, Enock Gomez, Mauricio Soto Casarighi, Elena et al.

Source: PLOS ONE. 20(5)

Subject Terms: Information and Computing Sciences, Biological Sciences, Bioinformatics and Computational Biology, Algorithms, Machine Learning, Semantics, Medical Informatics Computing, General Science & Technology

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Access URL: https://escholarship.org/uc/item/43k9s6k4
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A generalized covariate-adjusted top-scoring pair algorithm with applications to diabetic kidney disease stage classification in the Chronic Renal Insufficiency Cohort (CRIC) Study

Authors: Kwan, Brian Fuhrer, Tobias Montemayor, Daniel et al.

Source: BMC Bioinformatics. 24(1)

Subject Terms: Mathematical Sciences, Information and Computing Sciences, Statistics, Machine Learning, Kidney Disease, Diabetes, Clinical Research, Renal and urogenital, Humans, Diabetic Nephropathies, Betaine, Algorithms, Metabolomics, Renal Insufficiency, Chronic, Diabetes Mellitus, Biomarker, Classification, Feature selection, Kidney disease, Order statistics, Ranking algorithm, Biological Sciences, Bioinformatics, Biological sciences, Information and computing sciences, Mathematical sciences

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Systematic benchmarking of computational methods to identify spatially variable genes

Authors: Li, Zhijian M.Patel, Zain Song, Dongyuan et al.

Source: Genome Biology. 26(1)

Subject Terms: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Human Genome (rcdc), Genetics (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Benchmarking (mesh), Computational Biology (mesh), Algorithms (mesh), Gene Expression Profiling (mesh), Humans (mesh), Transcriptome (mesh), Benchmarking, Spatially variable genes, Simulation, Spatial omics, Visium, MERFISH, Humans (mesh), Gene Expression Profiling (mesh), Computational Biology (mesh), Algorithms (mesh), Benchmarking (mesh), Transcriptome (mesh), Benchmarking, MERFISH, Simulation, Spatial omics, Spatially variable genes, Visium, Benchmarking (mesh), Computational Biology (mesh), Algorithms (mesh), Gene Expression Profiling (mesh), Humans (mesh), Transcriptome (mesh), 05 Environmental Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix)

Access URL: https://escholarship.org/uc/item/16x872z6

Functional protein mining with conformal guarantees

Authors: Boger, Ron S Chithrananda, Seyone Angelopoulos, Anastasios N et al.

Source: Nature Communications. 16(1)

Subject Terms: 46 Information and Computing Sciences (for-2020), 3101 Biochemistry and Cell Biology (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 31 Biological Sciences (for-2020), Proteins (mesh), Algorithms (mesh), Computational Biology (mesh), Protein Conformation (mesh), Data Mining (mesh), Databases, Protein (mesh), Reproducibility of Results (mesh), Proteins (mesh), Reproducibility of Results (mesh), Computational Biology (mesh), Protein Conformation (mesh), Algorithms (mesh), Databases, Protein (mesh), Data Mining (mesh), Proteins (mesh), Algorithms (mesh), Computational Biology (mesh), Protein Conformation (mesh), Data Mining (mesh), Databases, Protein (mesh), Reproducibility of Results (mesh)

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Harnessing Tree Soft Set and Soft Computing Techniques' Capabilities in Bioinformatics: Analysis, Improvements, and Applications

Authors: Mona Gharib Fatima Rajab Mona Mohamed

Source: Neutrosophic Sets and Systems, Vol 61, Pp 579-597 (2023)

Subject Terms: bioinformatics, multiple sequence alignment, logic programming, multi-criteria decision-making, single value neutrosophic sets, tree soft sets, Mathematics, QA1-939, Electronic computers. Computer science, QA75.5-76.95

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Relation: https://fs.unm.edu/NSS/HarnessingTreeSoft30.pdf; https://doaj.org/toc/2331-6055; https://doaj.org/toc/2331-608X

Access URL: https://doaj.org/article/cbeaaf0f4e134c498b46955b2fa6702d

Bipartite tight spectral clustering (BiTSC) algorithm for identifying conserved gene co-clusters in two species

Authors: Sun, Yidan Eden Zhou, Heather J Li, Jingyi Jessica

Source: Bioinformatics. 37(9)

Subject Terms: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Genetics (rcdc), Bioengineering (rcdc), Generic health relevance (hrcs-hc), Algorithms (mesh), Animals (mesh), Cluster Analysis (mesh), Drosophila melanogaster (mesh), Gene Expression (mesh), Gene Expression Profiling (mesh), Animals (mesh), Drosophila melanogaster (mesh), Cluster Analysis (mesh), Gene Expression Profiling (mesh), Gene Expression (mesh), Algorithms (mesh), Algorithms (mesh), Animals (mesh), Cluster Analysis (mesh), Drosophila melanogaster (mesh), Gene Expression (mesh), Gene Expression Profiling (mesh), 01 Mathematical Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Bioinformatics (science-metrix), 31 Biological sciences (for-2020), 46 Information and computing sciences (for-2020), 49 Mathematical sciences (for-2020)

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ChromaFactor: Deconvolution of single-molecule chromatin organization with non-negative matrix factorization

Authors: Gunsalus, Laura M Keiser, Michael J Pollard, Katherine S

Source: PLOS Computational Biology. 21(2)

Subject Terms: Biochemistry and Cell Biology, Biological Sciences, Human Genome, Genetics, Biotechnology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Chromatin, Computational Biology, Humans, Single Molecule Imaging, Algorithms, Single-Cell Analysis, Mathematical Sciences, Information and Computing Sciences, Bioinformatics

Access URL: https://escholarship.org/uc/item/9cw1r2jr