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1
Protein sequence design with a learned potential
Protein sequence design with a learned potential
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Protein sequence design with a learned potential

Nature communications, 2022-02, Vol.13 (1), p.746-746, Article 746 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-022-28313-9 ;PMID: 35136054

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2
Fast and sensitive taxonomic classification for metagenomics with Kaiju
Fast and sensitive taxonomic classification for metagenomics with Kaiju
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Fast and sensitive taxonomic classification for metagenomics with Kaiju

Nature communications, 2016-04, Vol.7 (1), p.11257-11257, Article 11257 [Peer Reviewed Journal]

Copyright Nature Publishing Group Apr 2016 ;Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. 2016 Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/ncomms11257 ;PMID: 27071849

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3
ECNet is an evolutionary context-integrated deep learning framework for protein engineering
ECNet is an evolutionary context-integrated deep learning framework for protein engineering
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ECNet is an evolutionary context-integrated deep learning framework for protein engineering

Nature communications, 2021-09, Vol.12 (1), p.5743-14, Article 5743 [Peer Reviewed Journal]

2021. The Author(s). ;The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-021-25976-8 ;PMID: 34593817

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4
Accurately clustering biological sequences in linear time by relatedness sorting
Accurately clustering biological sequences in linear time by relatedness sorting
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Accurately clustering biological sequences in linear time by relatedness sorting

Nature communications, 2024-04, Vol.15 (1), p.3047-3047 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2024 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-024-47371-9 ;PMID: 38589369

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5
ProtGPT2 is a deep unsupervised language model for protein design
ProtGPT2 is a deep unsupervised language model for protein design
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ProtGPT2 is a deep unsupervised language model for protein design

Nature communications, 2022-07, Vol.13 (1), p.4348-4348, Article 4348 [Peer Reviewed Journal]

The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2022 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-022-32007-7 ;PMID: 35896542

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6
AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence
AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence
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AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence

Scientific reports, 2021-06, Vol.11 (1), p.12728-12728, Article 12728 [Peer Reviewed Journal]

This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-021-91456-0 ;PMID: 34135355

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7
HydDB: A web tool for hydrogenase classification and analysis
HydDB: A web tool for hydrogenase classification and analysis
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HydDB: A web tool for hydrogenase classification and analysis

Scientific reports, 2016-09, Vol.6 (1), p.34212-34212, Article 34212 [Peer Reviewed Journal]

Copyright Nature Publishing Group Sep 2016 ;Copyright © 2016, The Author(s) 2016 The Author(s) ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/srep34212 ;PMID: 27670643

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8
A 3.8 Å resolution cryo-EM structure of a small protein bound to an imaging scaffold
A 3.8 Å resolution cryo-EM structure of a small protein bound to an imaging scaffold
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A 3.8 Å resolution cryo-EM structure of a small protein bound to an imaging scaffold

Nature communications, 2019-04, Vol.10 (1), p.1864-1864, Article 1864 [Peer Reviewed Journal]

The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2019 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-019-09836-0 ;PMID: 31015551

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9
Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan
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Genomic characterization of the 2019 novel human-pathogenic coronavirus isolated from a patient with atypical pneumonia after visiting Wuhan

Emerging microbes & infections, 2020-01, Vol.9 (1), p.221-236 [Peer Reviewed Journal]

2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd 2020 ;2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd 2020 The Author(s) ;ISSN: 2222-1751 ;EISSN: 2222-1751 ;DOI: 10.1080/22221751.2020.1719902 ;PMID: 31987001

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10
Structure-based protein function prediction using graph convolutional networks
Structure-based protein function prediction using graph convolutional networks
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Structure-based protein function prediction using graph convolutional networks

Nature communications, 2021-05, Vol.12 (1), p.3168-3168, Article 3168 [Peer Reviewed Journal]

The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-021-23303-9 ;PMID: 34039967

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11
Transformer neural network for protein-specific de novo drug generation as a machine translation problem
Transformer neural network for protein-specific de novo drug generation as a machine translation problem
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Transformer neural network for protein-specific de novo drug generation as a machine translation problem

Scientific reports, 2021-01, Vol.11 (1), p.321-321, Article 321 [Peer Reviewed Journal]

The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-020-79682-4 ;PMID: 33432013

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12
Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties
Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties
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Ancestral sequence reconstruction produces thermally stable enzymes with mesophilic enzyme-like catalytic properties

Scientific reports, 2020-09, Vol.10 (1), p.15493-15493, Article 15493 [Peer Reviewed Journal]

The Author(s) 2020 ;ISSN: 2045-2322 ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-020-72418-4 ;PMID: 32968141

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13
Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody
Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody
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Potent binding of 2019 novel coronavirus spike protein by a SARS coronavirus-specific human monoclonal antibody

Emerging microbes & infections, 2020-01, Vol.9 (1), p.382-385 [Peer Reviewed Journal]

2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd 2020 ;2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd. This work is licensed under the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd 2020 The Author(s) ;ISSN: 2222-1751 ;EISSN: 2222-1751 ;DOI: 10.1080/22221751.2020.1729069 ;PMID: 32065055

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14
Inhibition of SARS-CoV-2 (previously 2019-nCoV) infection by a highly potent pan-coronavirus fusion inhibitor targeting its spike protein that harbors a high capacity to mediate membrane fusion
Inhibition of SARS-CoV-2 (previously 2019-nCoV) infection by a highly potent pan-coronavirus fusion inhibitor targeting its spike protein that harbors a high capacity to mediate membrane fusion
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Inhibition of SARS-CoV-2 (previously 2019-nCoV) infection by a highly potent pan-coronavirus fusion inhibitor targeting its spike protein that harbors a high capacity to mediate membrane fusion

Cell research, 2020-04, Vol.30 (4), p.343-355 [Peer Reviewed Journal]

The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 ;ISSN: 1001-0602 ;EISSN: 1748-7838 ;DOI: 10.1038/s41422-020-0305-x ;PMID: 32231345

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15
AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics
AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics
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AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics

Nature communications, 2022-11, Vol.13 (1), p.7238-7238, Article 7238 [Peer Reviewed Journal]

2022. The Author(s). ;The Author(s) 2022 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-022-34904-3 ;PMID: 36433986

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16
Clustering huge protein sequence sets in linear time
Clustering huge protein sequence sets in linear time
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Clustering huge protein sequence sets in linear time

Nature communications, 2018-06, Vol.9 (1), p.2542-8, Article 2542 [Peer Reviewed Journal]

2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2018 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-018-04964-5 ;PMID: 29959318

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17
Fusion mechanism of 2019-nCoV and fusion inhibitors targeting HR1 domain in spike protein
Fusion mechanism of 2019-nCoV and fusion inhibitors targeting HR1 domain in spike protein
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Fusion mechanism of 2019-nCoV and fusion inhibitors targeting HR1 domain in spike protein

Cellular & molecular immunology, 2020-07, Vol.17 (7), p.765-767 [Peer Reviewed Journal]

The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2020 ;ISSN: 1672-7681 ;EISSN: 2042-0226 ;DOI: 10.1038/s41423-020-0374-2 ;PMID: 32047258

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18
Protein design and variant prediction using autoregressive generative models
Protein design and variant prediction using autoregressive generative models
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Protein design and variant prediction using autoregressive generative models

Nature communications, 2021-04, Vol.12 (1), p.2403-2403, Article 2403 [Peer Reviewed Journal]

The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;The Author(s) 2021 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-021-22732-w ;PMID: 33893299

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19
Protein feature engineering framework for AMPylation site prediction
Protein feature engineering framework for AMPylation site prediction
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Protein feature engineering framework for AMPylation site prediction

Scientific reports, 2024-04, Vol.14 (1), p.8695-8695 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;EISSN: 2045-2322 ;DOI: 10.1038/s41598-024-58450-8 ;PMID: 38622194

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20
Cryo-EM structures of type IV pili complexed with nanobodies reveal immune escape mechanisms
Cryo-EM structures of type IV pili complexed with nanobodies reveal immune escape mechanisms
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Cryo-EM structures of type IV pili complexed with nanobodies reveal immune escape mechanisms

Nature communications, 2024-03, Vol.15 (1), p.2414-2414 [Peer Reviewed Journal]

2024. The Author(s). ;The Author(s) 2024. corrected publication 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;Attribution ;The Author(s) 2024 ;ISSN: 2041-1723 ;EISSN: 2041-1723 ;DOI: 10.1038/s41467-024-46677-y ;PMID: 38499587

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