Victor Lin
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Victor Lin has a total of 42 co-authors. Here are the top co-authors by number of shared publications:
- Artem Babaian
The Donnelly Centre for Cellular & Biomolecular Research, University of Toronto
2 shared publications Dan Lohr
Unaffiliated, Atlanta, GA, USA
2 shared publicationsGherman Novakovsky
Bioinformatics Graduate Program, University of British Columbia, Vancouver, British Columbia, Canada
2 shared publicationsJeff Taylor
Independent Researcher, Vancouver, British Columbia, Canada
2 shared publications- Jillian F. Banfield
Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
2 shared publications - Marcos de la Peña
Instituto de Biología Molecular y Celular de Plantas, Universidad Politécnica de Valencia-CSIC
2 shared publications
Latest Publications
- Open Access
Nextstrain automates real-time phylodynamic analysis of open data for endemic and emerging pathogens
Motivation: Genome sequencing provides an exceptional window into the evolutionary and epidemiological dynamics of endemic and emerging pathogens, and thus allows for better, more targeted, public health interventions. Online genomic surveillance platforms can provide near real-time insight into these dynamics. Results: Nextstrain provides continually updated real-time genomic surveillance for 21 viruses and the bacterial pathogen Mycobacterium tuberculosis, with most analyses relying solely on open sequence data. Each pathogen includes steps to fetch and curate open data, classify sequences using established nomenclature systems, perform phylodynamic analyses, and share the results publicly. These analyses are automated, with most running daily to provide continually updated snapshots of pathogen evolution. Availability and Implementation: All source code is available at https://github.com/nextstrain. Phylodynamic results can be visualized and downloaded at https://nextstrain.org/pathogens, and open sequence data and curated metadata are available at https://nextstrain.org/pathogens/files.
Open AccessNextstrain automates real-time phylodynamic analysis of open data for endemic and emerging pathogens
Motivation: Genome sequencing provides an exceptional window into the evolutionary and epidemiological dynamics of endemic and emerging pathogens, and thus allows for better, more targeted, public health interventions. Online genomic surveillance platforms can provide near real-time insight into these dynamics. Results: Nextstrain provides continually updated real-time genomic surveillance for 21 viruses and the bacterial pathogen Mycobacterium tuberculosis, with most analyses relying solely on open sequence data. Each pathogen includes steps to fetch and curate open data, classify sequences using established nomenclature systems, perform phylodynamic analyses, and share the results publicly. These analyses are automated, with most running daily to provide continually updated snapshots of pathogen evolution. Availability and Implementation: All source code is available at https://github.com/nextstrain. Phylodynamic results can be visualized and downloaded at https://nextstrain.org/pathogens, and open sequence data and curated metadata are available at https://nextstrain.org/pathogens/files.
- Top Cited Papers
- 26 January 2022
- Published by Springer Nature in Nature
- Vol. 602 (7895) , 142-147
Petabase-scale sequence alignment catalyses viral discovery
Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, which (at the time of writing) exceeds 20 petabases and is growing exponentially1. Here we developed a cloud computing infrastructure, Serratus, to enable ultra-high-throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA-dependent RNA polymerase and identified well over 105 novel RNA viruses, thereby expanding the number of known species by roughly an order of magnitude. We characterized novel viruses related to coronaviruses, hepatitis delta virus and huge phages, respectively, and analysed their environmental reservoirs. To catalyse the ongoing revolution of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.
- 26 January 2022
- Published by Springer Nature in Nature
- Vol. 602 (7895) , 142-147
Top Cited PapersPetabase-scale sequence alignment catalyses viral discovery
Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, which (at the time of writing) exceeds 20 petabases and is growing exponentially1. Here we developed a cloud computing infrastructure, Serratus, to enable ultra-high-throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA-dependent RNA polymerase and identified well over 105 novel RNA viruses, thereby expanding the number of known species by roughly an order of magnitude. We characterized novel viruses related to coronaviruses, hepatitis delta virus and huge phages, respectively, and analysed their environmental reservoirs. To catalyse the ongoing revolution of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.
- Open Access
Petabase-scale sequence alignment catalyses viral discovery
Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, now exceeding multiple petabases and growing exponentially [1, 2]. We developed a cloud computing infrastructure, Serratus , to enable ultra-high throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA dependent RNA polymerase, identifying well over 10 5 novel RNA viruses and thereby expanding the number of known species by roughly an order of magnitude. We characterised novel viruses related to coronaviruses and to hepatitis δ virus, respectively and explored their environmental reservoirs. To catalyse a new era of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.
Open AccessPetabase-scale sequence alignment catalyses viral discovery
Public databases contain a planetary collection of nucleic acid sequences, but their systematic exploration has been inhibited by a lack of efficient methods for searching this corpus, now exceeding multiple petabases and growing exponentially [1, 2]. We developed a cloud computing infrastructure, Serratus , to enable ultra-high throughput sequence alignment at the petabase scale. We searched 5.7 million biologically diverse samples (10.2 petabases) for the hallmark gene RNA dependent RNA polymerase, identifying well over 10 5 novel RNA viruses and thereby expanding the number of known species by roughly an order of magnitude. We characterised novel viruses related to coronaviruses and to hepatitis δ virus, respectively and explored their environmental reservoirs. To catalyse a new era of viral discovery, we established a free and comprehensive database of these data and tools. Expanding the known sequence diversity of viruses can reveal the evolutionary origins of emerging pathogens and improve pathogen surveillance for the anticipation and mitigation of future pandemics.