Suchergebnisse - "Software [MeSH]"

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

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

Quelle: Bioinformatics. 41(9)

Schlagwörter: 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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/1n5748bq
https://escholarship.org/content/qt1n5748bq/qt1n5748bq.pdf

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

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

Quelle: Bioinformatics. 41(7)

Schlagwörter: 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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/7b07t0b7
https://escholarship.org/content/qt7b07t0b7/qt7b07t0b7.pdf

BioPortal: an open community resource for sharing, searching, and utilizing biomedical ontologies

Autoren: Vendetti, Jennifer Harris, Nomi L Dorf, Michael V et al.

Quelle: Nucleic Acids Research. 53(W1)

Schlagwörter: 31 Biological Sciences (for-2020), 41 Environmental Sciences (for-2020), 34 Chemical Sciences (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), 1.5 Resources and infrastructure (underpinning) (hrcs-rac), Generic health relevance (hrcs-hc), Biological Ontologies (mesh), Internet (mesh), Information Dissemination (mesh), User-Computer Interface (mesh), Software (mesh), Databases, Factual (mesh), Humans (mesh), Humans (mesh), Information Dissemination (mesh), Internet (mesh), Software (mesh), User-Computer Interface (mesh), Databases, Factual (mesh), Biological Ontologies (mesh), Biological Ontologies (mesh), Internet (mesh), Information Dissemination (mesh), User-Computer Interface (mesh), Software (mesh), Databases, Factual (mesh), Humans (mesh), 05 Environmental Sciences (for), 06 Biological Sciences (for), 08 Information and Computing Sciences (for), Developmental Biology (science-metrix), 31 Biological sciences (for-2020), 34 Chemical sciences (for-2020), 41 Environmental sciences (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/86s6g6wf
https://escholarship.org/content/qt86s6g6wf/qt86s6g6wf.pdf

Highly accurate assembly polishing with DeepPolisher.

Autoren: Mastoras, Mira Asri, Mobin Brambrink, Lucas et al.

Quelle: Genome Research. 35(7)

Schlagwörter: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), Genetics (rcdc), Human Genome (rcdc), Humans (mesh), Genome, Human (mesh), Sequence Analysis, DNA (mesh), Software (mesh), High-Throughput Nucleotide Sequencing (mesh), Homozygote (mesh), Genomics (mesh), Algorithms (mesh), and the Human Pangenome Reference Consortium, Humans (mesh), Sequence Analysis, DNA (mesh), Genomics (mesh), Homozygote (mesh), Genome, Human (mesh), Algorithms (mesh), Software (mesh), High-Throughput Nucleotide Sequencing (mesh), Humans (mesh), Genome, Human (mesh), Sequence Analysis, DNA (mesh), Software (mesh), High-Throughput Nucleotide Sequencing (mesh), Homozygote (mesh), Genomics (mesh), Algorithms (mesh), 06 Biological Sciences (for), 11 Medical and Health Sciences (for), Bioinformatics (science-metrix), 3105 Genetics (for-2020)

Zugangs-URL: https://escholarship.org/uc/item/13z6x363

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Autoren: Kainer, David Lane, Matthew Sullivan, Kyle A et al.

Quelle: GigaScience. 14

Schlagwörter: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 1.5 Resources and infrastructure (underpinning) (hrcs-rac), Software (mesh), Computational Biology (mesh), Humans (mesh), Gene Regulatory Networks (mesh), Animals (mesh), Multiomics (mesh), multiplex network, systems biology, random walk with restart, multi-omic, software package, Animals (mesh), Humans (mesh), Computational Biology (mesh), Software (mesh), Gene Regulatory Networks (mesh), Multiomics (mesh), multi-omic, multiplex network, random walk with restart, software package, systems biology, Software (mesh), Computational Biology (mesh), Humans (mesh), Gene Regulatory Networks (mesh), Animals (mesh), Multiomics (mesh)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/8xf6s5bk
https://escholarship.org/content/qt8xf6s5bk/qt8xf6s5bk.pdf

Protocol for deep-learning-driven cell type label transfer in single-cell RNA sequencing data

Autoren: Zabetian, Zoe Gonzalez-Ferrer, Jesus Lehrer, Julian et al.

Quelle: STAR Protocols. 6(2)

Schlagwörter: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Human Genome (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Data Science (rcdc), Genetics (rcdc), Generic health relevance (hrcs-hc), Single-Cell Analysis (mesh), Sequence Analysis, RNA (mesh), Deep Learning (mesh), Software (mesh), Humans (mesh), pretrained models, Streamlit web app to, analyze results, influencing model, predictions, Humans (mesh), Sequence Analysis, RNA (mesh), Software (mesh), Single-Cell Analysis (mesh), Deep Learning (mesh), Developmental biology, RNA-seq, Sequencing, Single-Cell Analysis (mesh), Sequence Analysis, RNA (mesh), Deep Learning (mesh), Software (mesh), Humans (mesh)

Zugangs-URL: https://escholarship.org/uc/item/7qq7s0cg

GSLab: open-source platform for advanced phasor analysis in fluorescence microscopy

Autoren: Vallmitjana, Alexander Torrado, Belén Durkin, Amanda F et al.

Quelle: Bioinformatics. 41(4)

Schlagwörter: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 4601 Applied Computing (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Microscopy, Fluorescence (mesh), Software (mesh), Image Processing, Computer-Assisted (mesh), Machine Learning (mesh), Humans (mesh), Humans (mesh), Microscopy, Fluorescence (mesh), Image Processing, Computer-Assisted (mesh), Software (mesh), Machine Learning (mesh), Microscopy, Fluorescence (mesh), Software (mesh), Image Processing, Computer-Assisted (mesh), Machine Learning (mesh), Humans (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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/3q894731
https://escholarship.org/content/qt3q894731/qt3q894731.pdf

Image processing tools for petabyte-scale light sheet microscopy data

Autoren: Ruan, Xiongtao Mueller, Matthew Liu, Gaoxiang et al.

Quelle: Nature Methods. 21(12)

Schlagwörter: 31 Biological Sciences (for-2020), Biomedical Imaging (rcdc), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), 1.4 Methodologies and measurements (hrcs-rac), Generic health relevance (hrcs-hc), Software (mesh), Image Processing, Computer-Assisted (mesh), Microscopy (mesh), Imaging, Three-Dimensional (mesh), Animals (mesh), Humans (mesh), Algorithms (mesh), Animals (mesh), Humans (mesh), Imaging, Three-Dimensional (mesh), Microscopy (mesh), Algorithms (mesh), Image Processing, Computer-Assisted (mesh), Software (mesh), Software (mesh), Image Processing, Computer-Assisted (mesh), Microscopy (mesh), Imaging, Three-Dimensional (mesh), Animals (mesh), Humans (mesh), Algorithms (mesh), 06 Biological Sciences (for), 10 Technology (for), 11 Medical and Health Sciences (for), Developmental Biology (science-metrix), 31 Biological sciences (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/89g7x15j
https://escholarship.org/content/qt89g7x15j/qt89g7x15j.pdf

Personalized pangenome references

Autoren: Sirén, Jouni Eskandar, Parsa Ungaro, Matteo Tommaso et al.

Quelle: Nature Methods. 21(11)

Schlagwörter: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), Genetics (rcdc), Human Genome (rcdc), 2.1 Biological and endogenous factors (hrcs-rac), 3 Good Health and Well Being (sdg), Humans (mesh), Genome, Human (mesh), Software (mesh), Genetic Variation (mesh), Genomics (mesh), Haplotypes (mesh), Gene Frequency (mesh), Algorithms (mesh), High-Throughput Nucleotide Sequencing (mesh), Humans (mesh), Genomics (mesh), Gene Frequency (mesh), Haplotypes (mesh), Genome, Human (mesh), Algorithms (mesh), Software (mesh), Genetic Variation (mesh), High-Throughput Nucleotide Sequencing (mesh), Humans (mesh), Genome, Human (mesh), Software (mesh), Genetic Variation (mesh), Genomics (mesh), Haplotypes (mesh), Gene Frequency (mesh), Algorithms (mesh), High-Throughput Nucleotide Sequencing (mesh), 06 Biological Sciences (for), 10 Technology (for), 11 Medical and Health Sciences (for), Developmental Biology (science-metrix), 31 Biological sciences (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/2837z7n5
https://escholarship.org/content/qt2837z7n5/qt2837z7n5.pdf

Longitudinal registration of T1-weighted breast MRI: A registration algorithm (FLIRE) and clinical application

Autoren: Tong, Michelle W Yu, Hon J Sjaastad Andreassen, Maren M et al.

Quelle: Magnetic Resonance Imaging. 113

Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), 3211 Oncology and Carcinogenesis (for-2020), Women's Health (rcdc), Clinical Research (rcdc), Bioengineering (rcdc), Breast Cancer (rcdc), Cancer (rcdc), Biomedical Imaging (rcdc), 4.1 Discovery and preclinical testing of markers and technologies (hrcs-rac), Cancer (hrcs-hc), Humans (mesh), Algorithms (mesh), Breast Neoplasms (mesh), Female (mesh), Magnetic Resonance Imaging (mesh), Breast (mesh), Middle Aged (mesh), Longitudinal Studies (mesh), Neoadjuvant Therapy (mesh), Image Interpretation, Computer-Assisted (mesh), Reproducibility of Results (mesh), Adult (mesh), Image Processing, Computer-Assisted (mesh), Aged (mesh), Software (mesh), Non-linear, Registration, Longitudinal, Breast, Neoadjuvant chemotherapy, T1, Breast (mesh), Humans (mesh), Breast Neoplasms (mesh), Image Interpretation, Computer-Assisted (mesh), Magnetic Resonance Imaging (mesh), Neoadjuvant Therapy (mesh), Longitudinal Studies (mesh), Reproducibility of Results (mesh), Algorithms (mesh), Image Processing, Computer-Assisted (mesh), Software (mesh), Adult (mesh), Aged (mesh), Middle Aged (mesh), Female (mesh), Breast, Longitudinal, Neoadjuvant chemotherapy, Non-linear, Registration, T(1), Humans (mesh), Algorithms (mesh), Breast Neoplasms (mesh), Female (mesh), Magnetic Resonance Imaging (mesh), Breast (mesh), Middle Aged (mesh), Longitudinal Studies (mesh), Neoadjuvant Therapy (mesh), Image Interpretation, Computer-Assisted (mesh), Reproducibility of Results (mesh), Adult (mesh), Image Processing, Computer-Assisted (mesh), Aged (mesh), Software (mesh), 0903 Biomedical Engineering (for), 1103 Clinical Sciences (for), 1702 Cognitive Sciences (for), Nuclear Medicine & Medical Imaging (science-metrix), 3202 Clinical sciences (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/7mg2r6qb
https://escholarship.org/content/qt7mg2r6qb/qt7mg2r6qb.pdf

Interactive tools for functional annotation of bacterial genomes

Autoren: Price, Morgan N Arkin, Adam P

Quelle: Database. 2024

Schlagwörter: 3101 Biochemistry and Cell Biology (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), 31 Biological Sciences (for-2020), Biotechnology (rcdc), Genetics (rcdc), Human Genome (rcdc), 1.1 Normal biological development and functioning (hrcs-rac), Generic health relevance (hrcs-hc), Genome, Bacterial (mesh), Molecular Sequence Annotation (mesh), Software (mesh), Databases, Genetic (mesh), Bacterial Proteins (mesh), User-Computer Interface (mesh), Databases, Protein (mesh), Bacterial Proteins (mesh), Genome, Bacterial (mesh), Software (mesh), User-Computer Interface (mesh), Databases, Genetic (mesh), Databases, Protein (mesh), Molecular Sequence Annotation (mesh), Genome, Bacterial (mesh), Molecular Sequence Annotation (mesh), Software (mesh), Databases, Genetic (mesh), Bacterial Proteins (mesh), User-Computer Interface (mesh), Databases, Protein (mesh), 0804 Data Format (for), 0807 Library and Information Studies (for), 3102 Bioinformatics and computational biology (for-2020), 4605 Data management and data science (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/17c1h5kw
https://escholarship.org/content/qt17c1h5kw/qt17c1h5kw.pdf

Best practices to evaluate the impact of biomedical research software—metric collection beyond citations

Autoren: Afiaz, Awan Ivanov, Andrey A Chamberlin, John et al.

Quelle: Bioinformatics. 40(8)

Schlagwörter: 46 Information and Computing Sciences (for-2020), 4610 Library and Information Studies (for-2020), 4612 Software Engineering (for-2020), Bioengineering (rcdc), Cancer (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), 1.5 Resources and infrastructure (underpinning) (hrcs-rac), Generic health relevance (hrcs-hc), Cancer (hrcs-hc), 3 Good Health and Well Being (sdg), Software (mesh), Biomedical Research (mesh), Humans (mesh), United States (mesh), Computational Biology (mesh), Humans (mesh), Computational Biology (mesh), Biomedical Research (mesh), Software (mesh), United States (mesh), Software (mesh), Biomedical Research (mesh), Humans (mesh), United States (mesh), Computational Biology (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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/25h903r3
https://escholarship.org/content/qt25h903r3/qt25h903r3.pdf

GRIEVOUS: your command-line general for resolving cross-dataset genotype inconsistencies

Autoren: Talwar, James V Klie, Adam Pagadala, Meghana S et al.

Quelle: Bioinformatics. 40(8)

Schlagwörter: 31 Biological Sciences (for-2020), 3105 Genetics (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Human Genome (rcdc), Genetics (rcdc), Polymorphism, Single Nucleotide (mesh), Software (mesh), Genotype (mesh), Genome-Wide Association Study (mesh), Humans (mesh), Databases, Genetic (mesh), Alleles (mesh), Humans (mesh), Genotype (mesh), Polymorphism, Single Nucleotide (mesh), Alleles (mesh), Software (mesh), Databases, Genetic (mesh), Genome-Wide Association Study (mesh), Polymorphism, Single Nucleotide (mesh), Software (mesh), Genotype (mesh), Genome-Wide Association Study (mesh), Humans (mesh), Databases, Genetic (mesh), Alleles (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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/4b18n517
https://escholarship.org/content/qt4b18n517/qt4b18n517.pdf

Identification of mobile genetic elements with geNomad

Autoren: Camargo, Antonio Pedro Roux, Simon Schulz, Frederik et al.

Quelle: Nature Biotechnology. 42(8)

Schlagwörter: 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), Genetics (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), 3 Good Health and Well Being (sdg), Interspersed Repetitive Sequences (mesh), Plasmids (mesh), Software (mesh), Databases, Genetic (mesh), Molecular Sequence Annotation (mesh), Genome, Viral (mesh), Viruses (mesh), Neural Networks, Computer (mesh), Computational Biology (mesh), Viruses (mesh), Computational Biology (mesh), Interspersed Repetitive Sequences (mesh), Genome, Viral (mesh), Plasmids (mesh), Software (mesh), Databases, Genetic (mesh), Molecular Sequence Annotation (mesh), Neural Networks, Computer (mesh), Interspersed Repetitive Sequences (mesh), Plasmids (mesh), Software (mesh), Databases, Genetic (mesh), Molecular Sequence Annotation (mesh), Genome, Viral (mesh), Viruses (mesh), Neural Networks, Computer (mesh), Computational Biology (mesh)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/96n6w63s
https://escholarship.org/content/qt96n6w63s/qt96n6w63s.pdf

Likelihood-based interactive local docking into cryo-EM maps in ChimeraX

Autoren: Read, Randy J Pettersen, Eric F McCoy, Airlie J et al.

Quelle: Acta Crystallographica Section D, Structural Biology. 80(Pt 8)

Schlagwörter: 31 Biological Sciences (for-2020), 34 Chemical Sciences (for-2020), 51 Physical Sciences (for-2020), Cryoelectron Microscopy (mesh), Software (mesh), Molecular Docking Simulation (mesh), Protein Conformation (mesh), cryo-EM, docking, likelihood, ChimeraX, emplace_local, Cryoelectron Microscopy (mesh), Protein Conformation (mesh), Software (mesh), Molecular Docking Simulation (mesh), ChimeraX, cryo-EM, docking, emplace_local, likelihood, Cryoelectron Microscopy (mesh), Software (mesh), Molecular Docking Simulation (mesh), Protein Conformation (mesh)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/94j204sp
https://escholarship.org/content/qt94j204sp/qt94j204sp.pdf

Machine learning-based automated scan prescription of lumbar spine MRI acquisitions

Autoren: Ozhinsky, Eugene Liu, Felix Pedoia, Valentina et al.

Quelle: Magnetic Resonance Imaging. 110

Schlagwörter: 32 Biomedical and Clinical Sciences (for-2020), 3202 Clinical Sciences (for-2020), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), Machine Learning and Artificial Intelligence (rcdc), Clinical Research (rcdc), Biomedical Imaging (rcdc), Neurosciences (rcdc), Humans (mesh), Magnetic Resonance Imaging (mesh), Machine Learning (mesh), Lumbar Vertebrae (mesh), Low Back Pain (mesh), Image Processing, Computer-Assisted (mesh), Male (mesh), Female (mesh), Adult (mesh), Healthy Volunteers (mesh), Neural Networks, Computer (mesh), Software (mesh), Middle Aged (mesh), Magnetic resonance imaging, Automated prescription, Automated scan planning, Machine learning, Musculoskeletal MRI, Lumbar spine, Lumbar Vertebrae (mesh), Humans (mesh), Low Back Pain (mesh), Magnetic Resonance Imaging (mesh), Image Processing, Computer-Assisted (mesh), Software (mesh), Adult (mesh), Middle Aged (mesh), Female (mesh), Male (mesh), Healthy Volunteers (mesh), Machine Learning (mesh), Neural Networks, Computer (mesh), Automated prescription, Automated scan planning, Lumbar spine, Machine learning, Magnetic resonance imaging, Musculoskeletal MRI, Humans (mesh), Magnetic Resonance Imaging (mesh), Machine Learning (mesh), Lumbar Vertebrae (mesh), Low Back Pain (mesh), Image Processing, Computer-Assisted (mesh), Male (mesh), Female (mesh), Adult (mesh), Healthy Volunteers (mesh), Neural Networks, Computer (mesh), Software (mesh), Middle Aged (mesh), 0903 Biomedical Engineering (for), 1103 Clinical Sciences (for), 1702 Cognitive Sciences (for), Nuclear Medicine & Medical Imaging (science-metrix), 3202 Clinical sciences (for-2020)

Zugangs-URL: https://escholarship.org/uc/item/8x42d9br

Development of a Web-Based Interactive Tool for Visualizing Breast Cancer Clinical Trial Tolerability Data

Autoren: Luu, Michael Gresham, Gillian Henry, Lynn et al.

Quelle: JCO Clinical Cancer Informatics. 8(8)

Schlagwörter: 4203 Health Services and Systems (for-2020), 32 Biomedical and Clinical Sciences (for-2020), 42 Health Sciences (for-2020), 3211 Oncology and Carcinogenesis (for-2020), Women's Health (rcdc), Breast Cancer (rcdc), Clinical Trials and Supportive Activities (rcdc), Clinical Research (rcdc), Cancer (rcdc), Patient Safety (rcdc), Cancer (hrcs-hc), Humans (mesh), Breast Neoplasms (mesh), Female (mesh), Internet (mesh), Patient Reported Outcome Measures (mesh), Tamoxifen (mesh), User-Computer Interface (mesh), Software (mesh), Humans (mesh), Breast Neoplasms (mesh), Tamoxifen (mesh), Internet (mesh), Software (mesh), User-Computer Interface (mesh), Female (mesh), Patient Reported Outcome Measures (mesh), Humans (mesh), Breast Neoplasms (mesh), Female (mesh), Internet (mesh), Patient Reported Outcome Measures (mesh), Tamoxifen (mesh), User-Computer Interface (mesh), Software (mesh)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/2rg8593f
https://escholarship.org/content/qt2rg8593f/qt2rg8593f.pdf

Updates to the Alliance of Genome Resources central infrastructure.

Autoren: Carbon, seth

Quelle: Genetics. 227(1)

Schlagwörter: Animals, Caenorhabditis elegans, data integration, database, Databases, Drosophila, Genetic, Genome, Genomics, knowledgebase, Mice, mouse, software, Software, text mining, yeast, zebrafish, 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 3105 Genetics (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Genetics (rcdc), Machine Learning and Artificial Intelligence (rcdc), Biotechnology (rcdc), Human Genome (rcdc), Animals (mesh), Databases, Genetic (mesh), Genomics (mesh), Software (mesh), Genome (mesh), Mice (mesh), Alliance of Genome Resources Consortium, Animals (mesh), Mice (mesh), Genomics (mesh), Genome (mesh), Software (mesh), Databases, Genetic (mesh), Caenorhabditis elegans, Drosophila, data integration, database, knowledgebase, mouse, software, text mining, yeast, zebrafish, Animals (mesh), Databases, Genetic (mesh), Genomics (mesh), Software (mesh), Genome (mesh), Mice (mesh), 0604 Genetics (for), Developmental Biology (science-metrix), 3101 Biochemistry and cell biology (for-2020), 3105 Genetics (for-2020)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/1548r7x2
https://escholarship.org/content/qt1548r7x2/qt1548r7x2.pdf

PipeVal: light-weight extensible tool for file validation

Autoren: Patel, Yash Beshlikyan, Arpi Jordan, Madison et al.

Quelle: Bioinformatics. 40(2)

Schlagwörter: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), Networking and Information Technology R&D (NITRD) (rcdc), Bioengineering (rcdc), Software (mesh), Workflow (mesh), Software (mesh), Workflow (mesh), Software (mesh), Workflow (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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/6xm1x78s
https://escholarship.org/content/qt6xm1x78s/qt6xm1x78s.pdf

NFTest: automated testing of Nextflow pipelines

Autoren: Patel, Yash Zhu, Chenghao Yamaguchi, Takafumi N et al.

Quelle: Bioinformatics. 40(2)

Schlagwörter: 46 Information and Computing Sciences (for-2020), 31 Biological Sciences (for-2020), 3102 Bioinformatics and Computational Biology (for-2020), 4612 Software Engineering (for-2020), Bioengineering (rcdc), Networking and Information Technology R&D (NITRD) (rcdc), 3 Good Health and Well Being (sdg), Computational Biology (mesh), Software (mesh), Algorithms (mesh), Language (mesh), Workflow (mesh), Language (mesh), Computational Biology (mesh), Algorithms (mesh), Software (mesh), Workflow (mesh), Computational Biology (mesh), Software (mesh), Algorithms (mesh), Language (mesh), Workflow (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)

Dateibeschreibung: application/pdf

Zugangs-URL: https://escholarship.org/uc/item/3dj5x0wt
https://escholarship.org/content/qt3dj5x0wt/qt3dj5x0wt.pdf