Suchergebnisse - anzsrc-for: 3102 ((bioinformaticsa OR information) OR informatik) AND computational biology

How mandibular and hyoid morphology alters tongue muscle architecture in healthy adults: An anatomical atlas and statistical shape model of the tongue

Autoren: Lloyd, RA Dissanayake, E Jugé, L et al.

Quelle: urn:ISSN:0010-4825 ; urn:ISSN:1879-0534 ; Computers in Biology and Medicine, 189, 110006-110006

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, 4203 Health Services and Systems, 42 Health Sciences, 46 Information and Computing Sciences, 4601 Applied Computing, Biomedical Imaging, Dental/Oral and Craniofacial Disease, Clinical Research, Humans, Tongue, Male, Female, Adult, Hyoid Bone, Mandible, Magnetic Resonance Imaging, Models, Anatomic, Young Adult, Diffusion Magnetic Resonance Imaging, DWI, MRI, Muscle architecture, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 4203 Health Services and Systems, anzsrc-for: 42 Health Sciences, anzsrc-for: 46 Information and Computing Sciences, anzsrc-for: 4601 Applied Computing

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/1959.4/104552; https://doi.org/10.1016/j.compbiomed.2025.110006

Verfügbarkeit: https://hdl.handle.net/1959.4/104552
https://unsworks.unsw.edu.au/bitstreams/c5e53fcc-256f-485d-9ea2-bde0f2ddc61f/download
https://doi.org/10.1016/j.compbiomed.2025.110006

Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study

Autoren: Wang, X Zhang, Y Guo, T et al.

Quelle: urn:ISSN:0010-4825 ; urn:ISSN:1879-0534 ; Computers in Biology and Medicine, 176, 108556-108556

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, 4203 Health Services and Systems, 42 Health Sciences, 46 Information and Computing Sciences, 4601 Applied Computing, Neurosciences, Animals, Nerve Fibers, Myelinated, Unmyelinated, Rats, Electric Stimulation, Nanotubes, Carbon, Models, Neurological, Sciatic Nerve, Electrodes, Computational modeling, Intrafascicular electrical stimulation, Longitudinal electrode, Peripheral nerve, Selective activation, Unmyelinated C fiber, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 4203 Health Services and Systems, anzsrc-for: 42 Health Sciences, anzsrc-for: 46 Information and Computing Sciences

Relation: http://hdl.handle.net/1959.4/102145; https://doi.org/10.1016/j.compbiomed.2024.108556

Verfügbarkeit: http://hdl.handle.net/1959.4/102145
https://doi.org/10.1016/j.compbiomed.2024.108556

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Autoren: Duy Pham Xiao Tan Brad Balderson et al.

Quelle: Nat Commun
Nature Communications, Vol 14, Iss 1, Pp 1-25 (2023)

Schlagwörter: Neural Networks, 1.1 Normal biological development and functioning, Science, Gene Expression Profiling, Bioengineering, Cell Communication, Article, 3102 Bioinformatics and Computational Biology, Computer, Networking and Information Technology R&D (NITRD), Genetics, 2.1 Biological and endogenous factors, Neural Networks, Computer, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, Gene Expression Profiling/methods, Transcriptome, Software, Algorithms, 31 Biological Sciences, Cancer

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/38007580
https://doaj.org/article/90386dc9c14b4450ad2ce44635d342ec

Infectious disease mRNA vaccines and a review on epitope prediction for vaccine design

Autoren: Cai, Xinhui Li, Jiao Jiao Liu, Tao et al.

Quelle: Briefings in Functional Genomics. 20:289-303

Schlagwörter: 0301 basic medicine, Coronaviruses, Messenger, Coronaviruses Vaccines, Machine Learning, 3102 Bioinformatics and Computational Biology, epitope prediction, Epitopes, Neoplasms, Machine Learning and Artificial Intelligence, anzsrc-for: 31 Biological Sciences, Vaccines, 0303 health sciences, Zika Virus Infection, other infectious diseases, 3 Good Health and Well Being, 3. Good health, mRNA vaccines, Infectious Diseases, Networking and Information Technology R&D (NITRD), 3.4 Vaccines, Virus Diseases, Influenza Vaccines, Patient Safety, anzsrc-for: 3102 Bioinformatics and Computational Biology, Infection, Algorithms, Biotechnology, COVID-19 Vaccines, anzsrc-for: 0604 Genetics, Bioengineering, Dengue Vaccines, Cancer Vaccines, Vaccine Related, 03 medical and health sciences, Biodefense, Diabetes Mellitus, Respiratory Syncytial Virus Vaccines, Animals, Humans, RNA, Messenger, Pandemics, SARS-CoV-2, Prevention, COVID-19, Computational Biology, Vector-Borne Diseases, Emerging Infectious Diseases, Communicable Disease Control, RNA, Immunization, Software, 31 Biological Sciences

Dateibeschreibung: application/pdf

Zugangs-URL: https://academic.oup.com/bfg/article-pdf/20/5/289/40349787/elab027.pdf
https://pubmed.ncbi.nlm.nih.gov/34089044
https://pubmed.ncbi.nlm.nih.gov/34089044/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8194884
https://europepmc.org/article/PMC/PMC8194884
https://academic.oup.com/bfg/article/20/5/289/6292285
https://search.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/en/covidwho-1258749

Density-based detection of cell transition states to construct disparate and bifurcating trajectories

Autoren: Lan, T Hutvagner, G Zhang, X et al.

Quelle: urn:ISSN:0305-1048 ; urn:ISSN:1362-4962 ; Nucleic acids research, 50, 21, e122-e122

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Cancer Genomics, Genetics, Cancer, Human Genome, 1.1 Normal biological development and functioning, Humans, Single-Cell Analysis, SARS-CoV-2, COVID-19, Cell Differentiation, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 05 Environmental Sciences, anzsrc-for: 06 Biological Sciences, anzsrc-for: 08 Information and Computing Sciences, anzsrc-for: 34 Chemical sciences, anzsrc-for: 41 Environmental sciences

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/1959.4/unsworks_82561; https://doi.org/10.1093/nar/gkac785

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_82561
https://unsworks.unsw.edu.au/bitstreams/224bfec6-f949-406a-ab98-8a4c36cd4260/download
https://doi.org/10.1093/nar/gkac785

Application of network link prediction in drug discovery

Autoren: Abbas, K Abbasi, A Dong, S et al.

Quelle: urn:ISSN:1471-2105 ; BMC Bioinformatics, 22, 1

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Data Science, Patient Safety, Networking and Information Technology R&D (NITRD), Machine Learning and Artificial Intelligence, Bioengineering, 8.4 Research design and methodologies (health services), 1.4 Methodologies and measurements, Generic health relevance, 3 Good Health and Well Being, Algorithms, Drug Discovery, Drug Interactions, Machine Learning, Data-driven drug discovery, Drug-target prediction, Network link prediction, Poly-pharmacy, Poly-pharmacy side effects prediction, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 01 Mathematical Sciences, anzsrc-for: 06 Biological Sciences, anzsrc-for: 08 Information and Computing Sciences, anzsrc-for: 46 Information and computing sciences, anzsrc-for: 49 Mathematical sciences

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/1959.4/unsworks_83625

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_83625
https://unsworks.unsw.edu.au/bitstreams/f44db202-01dc-496a-ab08-28e7c8d1f8a2/download
https://doi.org/10.1186/s12859-021-04082-y

VIRMOTIF: A user-friendly tool for viral sequence analysis

Autoren: Rajaei, P Jahanian, KH Beheshti, A et al.

Quelle: urn:ISSN:2073-4425 ; Genes, 12, 2, 1-9

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Bioengineering, Networking and Information Technology R&D (NITRD), Biotechnology, 1.1 Normal biological development and functioning, 1.5 Resources and infrastructure (underpinning), Generic health relevance, Algorithms, Cluster Analysis, Computational Biology, Databases, Genetic, Genetic Variation, Genome, Viral, Nucleotide Motifs, Sequence Analysis, DNA, Software, User-Computer Interface, D-ratio, motif analysis, sequence variation, virus genome, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 0604 Genetics, anzsrc-for: 3105 Genetics

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/1959.4/unsworks_74948; https://doi.org/10.3390/genes12020186

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_74948
https://unsworks.unsw.edu.au/bitstreams/8a4858e8-873c-452e-bcab-004ab61cbac1/download
https://doi.org/10.3390/genes12020186

A generalised approach for high-throughput instance segmentation of stomata in microscope images

Autoren: Jayakody, H Petrie, P Boer, HJD et al.

Quelle: urn:ISSN:1746-4811 ; Plant Methods, 17, 1, 27

Schlagwörter: 30 Agricultural, Veterinary and Food Sciences, 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, 3108 Plant Biology, 3001 Agricultural Biotechnology, Bioengineering, Networking and Information Technology R&D (NITRD), Generic health relevance, Automatic stomata detection, High-throughput analysis, Instance segmentation, Machine learning, Mask R-CNN, Microscope imagery, anzsrc-for: 30 Agricultural, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 3108 Plant Biology, anzsrc-for: 3001 Agricultural Biotechnology, anzsrc-for: 0601 Biochemistry and Cell Biology, anzsrc-for: 0607 Plant Biology, anzsrc-for: 1001 Agricultural Biotechnology

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/1959.4/unsworks_75089

Verfügbarkeit: https://hdl.handle.net/1959.4/unsworks_75089
https://unsworks.unsw.edu.au/bitstreams/6eae025a-19fe-4b76-8b5b-7e150c819a0d/download
https://doi.org/10.1186/s13007-021-00727-4

Recognition of CRISPR/Cas9 off-target sites through ensemble learning of uneven mismatch distributions

Autoren: Peng, H Zheng, Y Zhao, Z et al.

Quelle: Bioinformatics. 34:i757-i765

Schlagwörter: 0301 basic medicine, anzsrc-for: 46 Information and computing sciences, Base Composition, Genome, anzsrc-for: 01 Mathematical Sciences, High-Throughput Nucleotide Sequencing, 3 Good Health and Well Being, anzsrc-for: 49 Mathematical sciences, RNA, Guide, CRISPR-Cas Systems, 3. Good health, Machine Learning, 3102 Bioinformatics and Computational Biology, 03 medical and health sciences, anzsrc-for: 06 Biological Sciences, RNA, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, CRISPR-Cas Systems, anzsrc-for: 08 Information and Computing Sciences, Guide, Software, 31 Biological Sciences, Biotechnology

Dateibeschreibung: application/pdf

Zugangs-URL: https://academic.oup.com/bioinformatics/article-pdf/34/17/i757/25702215/bty558.pdf
https://pubmed.ncbi.nlm.nih.gov/30423065
https://www.ncbi.nlm.nih.gov/pubmed/30423065
https://doi.org/10.1093/bioinformatics/bty558
https://pubmed.ncbi.nlm.nih.gov/30423065/
https://dblp.uni-trier.de/db/journals/bioinformatics/bioinformatics34.html#PengZZLL18
https://europepmc.org/article/MED/30423065
https://academic.oup.com/bioinformatics/article/34/17/i757/5093213

CoCoCoNet: Conserved and comparative co-expression across a diverse set of species

Autoren: Lee, J Shah, M Ballouz, S et al.

Quelle: urn:ISSN:0305-1048 ; urn:ISSN:1362-4962 ; Nucleic Acids Research, 48, W1, W566-W571

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Genetics, Mental Health, Biotechnology, Generic health relevance, Animals, Autism Spectrum Disorder, Gene Expression, Gene Regulatory Networks, Humans, RNA-Seq, Saccharomyces cerevisiae Proteins, Software, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 05 Environmental Sciences, anzsrc-for: 06 Biological Sciences, anzsrc-for: 08 Information and Computing Sciences, anzsrc-for: 34 Chemical sciences, anzsrc-for: 41 Environmental sciences

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/1959.4/unsworks_70355; https://doi.org/10.1093/NAR/GKAA348

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_70355
https://unsworks.unsw.edu.au/bitstreams/4a336961-d282-4b92-b398-21430731a8e3/download
https://doi.org/10.1093/NAR/GKAA348

Automated detection of pneumoconiosis with multilevel deep features learned from chest X-Ray radiographs

Autoren: Devnath, L Luo, S Summons, P et al.

Quelle: urn:ISSN:0010-4825 ; urn:ISSN:1879-0534 ; Computers in Biology and Medicine, 129, 104125

Schlagwörter: 4611 Machine Learning, 46 Information and Computing Sciences, 4603 Computer Vision and Multimedia Computation, Bioengineering, Machine Learning and Artificial Intelligence, Networking and Information Technology R&D (NITRD), Biomedical Imaging, 4.1 Discovery and preclinical testing of markers and technologies, Humans, Pneumoconiosis, Radiographic Image Interpretation, Computer-Assisted, Radiography, Support Vector Machine, X-Rays, Black lung, Coal workers' pneumoconiosis (CWP), Computer-aided diagnosis, Deep transfer learning, anzsrc-for: 4611 Machine Learning, anzsrc-for: 46 Information and Computing Sciences, anzsrc-for: 4603 Computer Vision and Multimedia Computation, anzsrc-for: 08 Information and Computing Sciences, anzsrc-for: 09 Engineering, anzsrc-for: 11 Medical and Health Sciences, anzsrc-for: 3102 Bioinformatics and computational biology, anzsrc-for: 4203 Health services and systems, anzsrc-for: 4601 Applied computing

Relation: https://hdl.handle.net/1959.4/unsworks_75477; https://doi.org/10.1016/j.compbiomed.2020.104125

Verfügbarkeit: https://hdl.handle.net/1959.4/unsworks_75477
https://doi.org/10.1016/j.compbiomed.2020.104125

Evaluation of cross-platform and interlaboratory concordance via consensus modelling of genomic measurements

Autoren: Ruth Pidsley Tim J Peters Wenjia Qu et al.

Weitere Verfasser: Ruth Pidsley Tim J Peters Wenjia Qu et al.

Quelle: Bioinformatics

Schlagwörter: 0301 basic medicine, Bioengineering, anzsrc-for: 49 Mathematical sciences, 3105 Genetics, 3102 Bioinformatics and Computational Biology, 03 medical and health sciences, Genetics, Humans, anzsrc-for: 31 Biological Sciences, Oligonucleotide Array Sequence Analysis, anzsrc-for: 46 Information and computing sciences, Genome, Genome, Human, Human Genome, anzsrc-for: 01 Mathematical Sciences, Computational Biology, Genomics, DNA Methylation, Original Papers, anzsrc-for: 3105 Genetics, anzsrc-for: 06 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 08 Information and Computing Sciences, Software, 31 Biological Sciences, Biotechnology, Human

Dateibeschreibung: application/pdf

Zugangs-URL: https://academic.oup.com/bioinformatics/article-pdf/35/4/560/27838576/bty675.pdf
https://pubmed.ncbi.nlm.nih.gov/30084929
https://minerva-access.unimelb.edu.au/handle/11343/271038
https://europepmc.org/articles/PMC6378945
https://pubmed.ncbi.nlm.nih.gov/30084929/
https://dblp.uni-trier.de/db/journals/bioinformatics/bioinformatics35.html#PetersFBPSVNQSG19
https://findanexpert.unimelb.edu.au/scholarlywork/1345377-evaluation-of-cross-platform-and-interlaboratory-concordance-via-consensus-modelling-of-genomic-measurements
https://minerva-access.unimelb.edu.au/bitstream/handle/11343/271038/PMC6378945.pdf

An ensemble of locally reliable cluster solutions

Autoren: Niu, H Khozouie, N Parvin, H et al.

Quelle: urn:ISSN:2076-3417 ; Applied Sciences (Switzerland), 10, 5, 1891

Schlagwörter: 46 Information and Computing Sciences, 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, anzsrc-for: 46 Information and Computing Sciences, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology

Dateibeschreibung: application/pdf

Relation: http://hdl.handle.net/1959.4/unsworks_69039; https://doi.org/10.3390/app10051891

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_69039
https://unsworks.unsw.edu.au/bitstreams/a1c6d964-efad-4dd5-ba67-56264ef92c0b/download
https://doi.org/10.3390/app10051891

MHiC, an integrated user-friendly tool for the identification and visualization of significant interactions in Hi-C data

Autoren: Khakmardan, S Rezvani, M Pouyan, AA et al.

Quelle: urn:ISSN:1471-2164 ; BMC Genomics, 21, 1, 225

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Algorithms, Chromatin, Chromosomes, Computational Biology, Humans, Models, Molecular, Molecular Conformation, User-Computer Interface, Chromosome conformation capture, Contact map, Hi-C, Hi-C data visualization, Statistically significant interactions, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 06 Biological Sciences, anzsrc-for: 08 Information and Computing Sciences, anzsrc-for: 11 Medical and Health Sciences, anzsrc-for: 32 Biomedical and clinical sciences

Dateibeschreibung: application/pdf

Relation: https://hdl.handle.net/1959.4/unsworks_69059

Verfügbarkeit: https://hdl.handle.net/1959.4/unsworks_69059
https://unsworks.unsw.edu.au/bitstreams/9abb79ec-210a-4f24-97be-0acbd8520df0/download
https://doi.org/10.1186/s12864-020-6636-7

Adaptation of Oxford Nanopore technology for hepatitis C whole genome sequencing and identification of within-host viral variants

Autoren: Rowena A. Bull Kirston Barton Andrew R. Lloyd et al.

Quelle: BMC Genomics
BMC Genomics, Vol 22, Iss 1, Pp 1-12 (2021)

Schlagwörter: 0301 basic medicine, Technology, Bioengineering, QH426-470, 3105 Genetics, Hepatitis, 3102 Bioinformatics and Computational Biology, Nanopores, 03 medical and health sciences, Hepatitis - C, Genetics, Nanotechnology, 2.1 Biological and endogenous factors, Humans, Nano-Q, anzsrc-for: 31 Biological Sciences, Phylogeny, 0303 health sciences, Whole Genome Sequencing, Hepatitis C virus, Liver Disease, Human Genome, High-Throughput Nucleotide Sequencing, 3 Good Health and Well Being, DNA, Sequence Analysis, DNA, Hepatitis C, 3. Good health, Oxford Nanopore technology, anzsrc-for: 3105 Genetics, anzsrc-for: 32 Biomedical and clinical sciences, Infectious Diseases, Emerging Infectious Diseases, Cost Effectiveness Research, anzsrc-for: 11 Medical and Health Sciences, Haplotypes, anzsrc-for: 06 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, Third generation sequencing, Digestive Diseases, Infection, anzsrc-for: 08 Information and Computing Sciences, Sequence Analysis, TP248.13-248.65, 31 Biological Sciences, Biotechnology, Research Article

Dateibeschreibung: application/pdf

Zugangs-URL: https://bmcgenomics.biomedcentral.com/track/pdf/10.1186/s12864-021-07460-1
https://pubmed.ncbi.nlm.nih.gov/33653280
https://doaj.org/article/27ac5a45c50a4b9891f2a9cec58eaa4c
https://link.springer.com/content/pdf/10.1186/s12864-021-07460-1.pdf
https://pubmed.ncbi.nlm.nih.gov/33653280/
https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-021-07460-1
https://link.springer.com/article/10.1186/s12864-021-07460-1
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923462
https://europepmc.org/article/MED/33653280

Sequencing dropout-and-batch effect normalization for single-cell mRNA profiles: a survey and comparative analysis

Autoren: Lan, Tian Hutvagner, Gyorgy Lan, Qing et al.

Quelle: urn:ISSN:1467-5463 ; urn:ISSN:1477-4054 ; Briefings in Bioinformatics, 22, 4, bbaa248

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Human Genome, Genetics, Generic health relevance, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis, RNA, Messenger, Single-Cell Analysis, Software, Transcriptome, batch effect, dropout, normalization tools, performance evaluation, single-cell mRNA sequencing, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology, anzsrc-for: 0601 Biochemistry and Cell Biology, anzsrc-for: 0802 Computation Theory and Mathematics, anzsrc-for: 0899 Other Information and Computing Sciences, anzsrc-for: 3101 Biochemistry and cell biology, anzsrc-for: 3105 Genetics

Dateibeschreibung: application/pdf

Relation: http://purl.org/au-research/grants/nhmrc/APP1106790; http://purl.org/au-research/grants/nhmrc/APP1099025; http://purl.org/au-research/grants/nhmrc/APP1120936; https://doi-org.wwwproxy1.library.unsw.edu.au/10.1093/bib/bbaa248; https://hdl.handle.net/1959.4/unsworks_74169; https://doi.org/10.1093/bib/bbaa248

Verfügbarkeit: https://hdl.handle.net/1959.4/unsworks_74169
https://unsworks.unsw.edu.au/bitstreams/5c17f82f-96ce-4ea7-97bd-922be7872cc3/download
https://doi.org/10.1093/bib/bbaa248

Maximum likelihood estimates of pairwise rearrangement distances

Autoren: Barbara R. Holland Mark M. Tanaka Stuart Serdoz et al.

Weitere Verfasser: Barbara R. Holland Mark M. Tanaka Stuart Serdoz et al.

Quelle: Journal of Theoretical Biology. 423:31-40

Schlagwörter: 0301 basic medicine, 20P05, 60B15, Evolution, 0206 medical engineering, group theory, Group Theory (math.GR), 02 engineering and technology, Genome rearrangement, anzsrc-for: 49 Mathematical sciences, algebra, phylogeny, Quantitative Biology - Quantitative Methods, 3105 Genetics, Evolution, Molecular, 3102 Bioinformatics and Computational Biology, 03 medical and health sciences, FOS: Mathematics, anzsrc-for: 31 Biological Sciences, 970106 - Expanding Knowledge in the Biological Sciences, Quantitative Biology - Populations and Evolution, Phylogeny, Quantitative Methods (q-bio.QM), Likelihood Functions, Spatial Analysis, Genome, anzsrc-for: 01 Mathematical Sciences, Probability (math.PR), Inversion, Populations and Evolution (q-bio.PE), Molecular, anzsrc-for: 3105 Genetics, 010105 - Group Theory and Generalisations, FOS: Biological sciences, anzsrc-for: 06 Biological Sciences, Group theory, anzsrc-for: 3102 Bioinformatics and Computational Biology, 010202 - Biological Mathematics, anzsrc-for: 08 Information and Computing Sciences, genomes, Mathematics - Group Theory, Algebraic biology, Mathematics - Probability, 31 Biological Sciences, Coset, Maximum likelihood

Dateibeschreibung: print; application/pdf

Zugangs-URL: https://eprints.utas.edu.au/25713/1/genomelikelihood.pdf
https://pubmed.ncbi.nlm.nih.gov/28435014
http://arxiv.org/abs/1602.03962
http://ecite.utas.edu.au/116013
https://www.ncbi.nlm.nih.gov/pubmed/28435014
https://eprints.utas.edu.au/25713/
http://www.sciencedirect.com/science/article/pii/S0022519317301790
https://www.sciencedirect.com/science/article/pii/S0022519317301790
https://europepmc.org/article/MED/28435014

MetaLIMS, a simple open-source laboratory information management system for small metagenomic labs

Autoren: Heinle, CE Gaultier, NPE Miller, D et al.

Quelle: urn:ISSN:2047-217X ; GigaScience, 6, 6, gix025-6

Schlagwörter: 31 Biological Sciences, 3102 Bioinformatics and Computational Biology, Networking and Information Technology R&D (NITRD), Genetics, Database Management Systems, Internet, Laboratories, Management Information Systems, Metagenomics, Software, User-Computer Interface, GitHub, HTML, JavaScript, LIMS, customizable, mysql, open-source, php, sample management, web application, anzsrc-for: 31 Biological Sciences, anzsrc-for: 3102 Bioinformatics and Computational Biology

Relation: http://hdl.handle.net/1959.4/unsworks_53774; https://doi.org/10.1093/gigascience/gix025

Verfügbarkeit: http://hdl.handle.net/1959.4/unsworks_53774
https://doi.org/10.1093/gigascience/gix025

Small RNA interactome of pathogenic E. coli revealed through crosslinking of RNase E

Autoren: Waters, SA McAteer, SP Kudla, G et al.

Quelle: EMBO J
Waters, S A, McAteer, S P, Kudla, G, Pang, I, Deshpande, N P, Amos, T G, Leong, K W, Wilkins, M R, Strugnell, R, Gally, D L, Tollervey, D & Tree, J J 2017, ' Small RNA interactome of pathogenic E. coli revealed through crosslinking of RNase E ', EMBO Journal, vol. 36, no. 3, pp. 374-387 . https://doi.org/10.15252/embj.201694639

Schlagwörter: Resource, 0301 basic medicine, enterohaemorrhagic E. coli, CLIP-Seq, Messenger, non-coding RNA, CLIP‐Seq, 3102 Bioinformatics and Computational Biology, 03 medical and health sciences, Endoribonucleases, Genetics, Escherichia coli, 2.2 Factors relating to the physical environment, 2.1 Biological and endogenous factors, RNA, Messenger, anzsrc-for: 31 Biological Sciences, 0303 health sciences, Bacterial, DNA, Gene Expression Regulation, Bacterial, Sequence Analysis, DNA, CRAC, 3. Good health, Small Untranslated, anzsrc-for: 32 Biomedical and clinical sciences, Gene Expression Regulation, anzsrc-for: 11 Medical and Health Sciences, non‐coding RNA, anzsrc-for: 06 Biological Sciences, RNA, EHEC, RNA, Small Untranslated, anzsrc-for: 3102 Bioinformatics and Computational Biology, Infection, anzsrc-for: 08 Information and Computing Sciences, Sequence Analysis, 31 Biological Sciences, Protein Binding

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/27836995
https://www.embopress.org/doi/full/10.15252/embj.201694639
http://onlinelibrary.wiley.com/doi/10.15252/embj.201694639/full
https://www.onlinelibrary.wiley.com/doi/10.15252/embj.201694639
https://emboj.embopress.org/content/36/3/374
https://minerva-access.unimelb.edu.au/bitstream/handle/11343/260950/PMC5286369.pdf
https://www.ncbi.nlm.nih.gov/pubmed/27836995
https://www.pure.ed.ac.uk/ws/files/28923683/embj.201694639.full.pdf
https://hdl.handle.net/20.500.11820/e697ac02-77f4-46c0-9088-3cdbe134d298

VDJdb: a curated database of T-cell receptor sequences with known antigen specificity: a curated database of T-cell receptor sequences with known antigen specificity

Autoren: Kristin Ladell Evgeniy S. Egorov Meriem Attaf et al.

Weitere Verfasser: Kristin Ladell Evgeniy S. Egorov Meriem Attaf et al.

Quelle: Nucleic Acids Res
Nucleic Acids Research

Schlagwörter: Models, Molecular, 0301 basic medicine, Secondary, T-Lymphocytes, Sequence Homology, Protein Structure, Secondary, Major Histocompatibility Complex, 3102 Bioinformatics and Computational Biology, Mice, 0302 clinical medicine, Models, Receptors, Database Issue, anzsrc-for: 31 Biological Sciences, Databases, Protein, High-Throughput Nucleotide Sequencing, 3. Good health, anzsrc-for: 41 Environmental sciences, Amino Acid, Antigen, anzsrc-for: 3102 Bioinformatics and Computational Biology, Single-Cell Analysis, Biotechnology, Protein Binding, Protein Structure, Receptors, Antigen, T-Cell, Databases, 03 medical and health sciences, anzsrc-for: 34 Chemical sciences, Genetics, Animals, Humans, Protein Interaction Domains and Motifs, Amino Acid Sequence, Antigens, Internet, Binding Sites, Sequence Homology, Amino Acid, Protein, Molecular, anzsrc-for: 05 Environmental Sciences, Molecular Sequence Annotation, T-Cell, Macaca mulatta, anzsrc-for: 06 Biological Sciences, anzsrc-for: 08 Information and Computing Sciences, Sequence Alignment, Software, 31 Biological Sciences

Dateibeschreibung: application/pdf; image/pdf

Zugangs-URL: https://academic.oup.com/nar/article-pdf/46/D1/D419/23162525/gkx760.pdf
https://pubmed.ncbi.nlm.nih.gov/28977646
https://research-portal.uu.nl/en/publications/ff3bc28c-d8e3-4d70-9c62-3beb24c71fa3
https://doi.org/10.1093/nar/gkx760
https://minerva-access.unimelb.edu.au/bitstream/handle/11343/222151/VDJdb a curated database of T-cell receptor sequences with known antigen specificity.pdf
http://academic.oup.com/nar/article/46/D1/D419/4101254
https://dissem.in/p/107541846/vdjdb-a-curated-database-of-t-cell-receptor-sequences-with-known-antigen-specificity/
https://findanexpert.unimelb.edu.au/scholarlywork/1256493-vdjdb--a-curated-database-of-t-cell-receptor-sequences-with-known-antigen-specificity
https://orca.cardiff.ac.uk/104554/
https://academic.oup.com/nar/article/46/D1/D419/4101254
https://dspace.library.uu.nl/handle/1874/376457
https://hdl.handle.net/10029/621387