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Refinado por: assunto: Life Sciences & Biomedicine remover assunto: Mathematical & Computational Biology remover Base de dados/Biblioteca: Oxford Journals remover
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1
Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience
Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience
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Ultraliser: a framework for creating multiscale, high-fidelity and geometrically realistic 3D models for in silico neuroscience

Abdellah, Marwan ; Cantero, Juan José García ; Guerrero, Nadir Román ; Foni, Alessandro ; Coggan, Jay S ; Calì, Corrado ; Agus, Marco ; Zisis, Eleftherios ; Keller, Daniel ; Hadwiger, Markus ; Magistretti, Pierre J ; Markram, Henry ; Schürmann, Felix

Briefings in bioinformatics, 2023-01, Vol.24 (1) [Periódico revisado por pares]

England

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2
In silico binding profile characterization of SARS-CoV-2 spike protein and its mutants bound to human ACE2 receptor
In silico binding profile characterization of SARS-CoV-2 spike protein and its mutants bound to human ACE2 receptor
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In silico binding profile characterization of SARS-CoV-2 spike protein and its mutants bound to human ACE2 receptor

Zhang, Yuzhao ; He, Xibing ; Zhai, Jingchen ; Ji, Beihong ; Man, Viet Hoang ; Wang, Junmei

Briefings in bioinformatics, 2021-11, Vol.22 (6) [Periódico revisado por pares]

England: Oxford University Press

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3
GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit
GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit
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GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit

Pronk, Sander ; Páll, Szilárd ; Schulz, Roland ; Larsson, Per ; Bjelkmar, Pär ; Apostolov, Rossen ; Shirts, Michael R ; Smith, Jeremy C ; Kasson, Peter M ; van der Spoel, David ; Hess, Berk ; Lindahl, Erik

Bioinformatics, 2013-04, Vol.29 (7), p.845-854 [Periódico revisado por pares]

England: Oxford University Press

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4
ABC random forests for Bayesian parameter inference
ABC random forests for Bayesian parameter inference
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ABC random forests for Bayesian parameter inference

Raynal, Louis ; Marin, Jean-Michel ; Pudlo, Pierre ; Ribatet, Mathieu ; Robert, Christian P ; Estoup, Arnaud Stegle, Oliver

Bioinformatics, 2019-05, Vol.35 (10), p.1720-1728 [Periódico revisado por pares]

England: Oxford University Press

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5
A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation
A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation
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A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation

Rakib, Ahmed ; Nain, Zulkar ; Sami, Saad Ahmed ; Mahmud, Shafi ; Islam, Ashiqul ; Ahmed, Shahriar ; Siddiqui, Adnan Bin Faisul ; Babu, S M Omar Faruque ; Hossain, Payar ; Shahriar, Asif ; Nainu, Firzan ; Emran, Talha Bin ; Simal-Gandara, Jesus

Briefings in bioinformatics, 2021-03, Vol.22 (2), p.1476-1498 [Periódico revisado por pares]

England: Oxford University Press

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6
Multivariate output analysis for Markov chain Monte Carlo
Multivariate output analysis for Markov chain Monte Carlo
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Multivariate output analysis for Markov chain Monte Carlo

Vats, Dootika ; Flegal, James M ; Jones, Galin L

Biometrika, 2019-06, Vol.106 (2), p.321-337 [Periódico revisado por pares]

Oxford: Oxford University Press

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7
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA
Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA
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Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

Kelly, Brendan J ; Gross, Robert ; Bittinger, Kyle ; Sherrill-Mix, Scott ; Lewis, James D ; Collman, Ronald G ; Bushman, Frederic D ; Li, Hongzhe

Bioinformatics, 2015-08, Vol.31 (15), p.2461-2468 [Periódico revisado por pares]

England: Oxford University Press

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8
Novel ChIP-seq simulating program with superior versatility: isChIP
Novel ChIP-seq simulating program with superior versatility: isChIP
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Novel ChIP-seq simulating program with superior versatility: isChIP

Subkhankulova, Tatiana ; Naumenko, Fedor ; Tolmachov, Oleg E ; Orlov, Yuriy L

Briefings in bioinformatics, 2021-07, Vol.22 (4) [Periódico revisado por pares]

England: Oxford University Press

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9
Computational/in silico methods in drug target and lead prediction
Computational/in silico methods in drug target and lead prediction
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Computational/in silico methods in drug target and lead prediction

Agamah, Francis E ; Mazandu, Gaston K ; Hassan, Radia ; Bope, Christian D ; Thomford, Nicholas E ; Ghansah, Anita ; Chimusa, Emile R

Briefings in bioinformatics, 2020-09, Vol.21 (5), p.1663-1675 [Periódico revisado por pares]

England: Oxford University Press

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10
SpatialcoGCN: deconvolution and spatial information–aware simulation of spatial transcriptomics data via deep graph co-embedding
SpatialcoGCN: deconvolution and spatial information–aware simulation of spatial transcriptomics data via deep graph co-embedding
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SpatialcoGCN: deconvolution and spatial information–aware simulation of spatial transcriptomics data via deep graph co-embedding

Yin, Wang ; Wan, You ; Zhou, Yuan

Briefings in bioinformatics, 2024-03, Vol.25 (3) [Periódico revisado por pares]

England: Oxford University Press

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