Alan Williams

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About Alan Williams:

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SEEK ID: https://workflowhub.eu/people/6

Location: United Kingdom

ORCID: Not specified

Joined: 7th Apr 2020

Expertise: Not specified

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EOSC-Life

EOSC-Life brings together the 13 Life Science ‘ESFRI’ research infrastructures (LS RIs) to create an open, digital and collaborative space for biological and medical research.

The project will publish ‘FAIR’ data and a catalogue of services provided by participating RIs for the management, storage and reuse of data in the European Open Science Cloud (EOSC).

Teams: EOSC-Life - Demonstrator 7: Rare Diseases, EOSC-Life WP3

Web page: https://www.eosc-life.eu/

Independent Teams

A space managed by WorkflowHub administrators for teams that don't want/need to manage their own space.

Teams: IBISBA Workflows, NMR Workflow, UNLOCK, NanoGalaxy, Galaxy Climate, PNDB, IMBforge, COVID-19 PubSeq: Public SARS-CoV-2 Sequence Resource, LBI-RUD, Nick-test-team, usegalaxy-eu, Italy-Covid-data-Portal, UX trial team, Integrated and Urban Plant Pathology Laboratory, SARS-CoV-2 Data Hubs, lmjxteam2, virAnnot pipeline, Ay Lab, iPC: individualizedPaediatricCure, Harkany Lab, Genomics Coordination Center, EJPRD WP13 case-studies workflows, Common Workflow Language (CWL) community, Testing, SeBiMER, IAA-CSIC, MAB - ATGC, Probabilistic graphical models, GenX, Snakemake-Workflows, ODA, IPK BIT, CO2MICS Lab, FAME, CHU Limoges - UF9481 Bioinformatique / CNR Herpesvirus, Quadram Institute Bioscience - Bioinformatics, HecatombDevelopment, Institute of Human Genetics, Testing RO Crates, Test Team, Applied Computational Biology at IEG/HMGU, INFRAFRONTIER workflows, OME, TransBioNet, OpenEBench, Galaxycompchem, Bioinformatics and Biostatistics (BIO2 ) Core, VIB Bioinformatics Core, CRC Cohort, ICAN, MustafaVoh, Single Cell Unit, CO-Graph, emo-bon, TestEMBL-EBIOntology, CINECA, Toxicology community, Pitagora-Network, Workflows Australia, Medizinisches Proteom-Center, Medical Bioinformatics, AGRF BIO, EU-Openscreen, X-omics, ELIXIR Belgium, URGI, Size Inc, GA-VirReport Team, The Boucher Lab, Cluster Emergent del Cervell Humà, Air Quality Prediction, pyiron, CAPSID, Edinburgh Genomics, Defragmentation TS, NBIS, Phytoplankton Analysis, Seq4AMR, Workflow registry test, Read2Map, SKM3, ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression, de.NBI Cloud, Meta-NanoSim, ILVO Plant Health, EMERGEN-BIOINFO, KircherLab, Apis-wings, BCCM_ULC, Dessimoz Lab, TRON gGmbH, GEMS at MLZ, Computational Science at HZDR, Big data in biomedicine, TRE-FX, MISTIC, Guigó lab, Statistical genetics, Delineating Regions-of-interest for Mass Spectrometry Imaging by Multimodally Corroborated Spatial Segmentation, DLSW, Bioinformatics Unit @ CRG, Bioinformatics Innovation Lab, BSC-CES, ELIXIR Proteomics, Black Ochre Data Labs, Zavolan Lab, Metabolomics-Reproducibility, Team Cardio, NGFF Tools, Bioinformatics workflows for life science, Workflows for geographic science, Pacific-deep-sea-sponges-microbiome, CSFG, SNAKE, Katdetectr, INFRAFRONTIER GmbH, PerMedCoE, EuroScienceGateway

Web page: Not specified

COVID-19 Biohackathon

The goal of COVID-19-Biohackathon 2020 (COVID-19-BH20) is to develop and gather computational tools that can be useful for studying the biology of the virus and the disease.

The COVID-19 Programme in Workflow Hub aims to gather workflows for the analysis of COVID-19 molecular biology data and their metadata. In this programme, all workflows and their metadata will be curated and made interoperable, reusable and reproducible. All workflows and their metadata will be easily accessible to everyone ...

Teams: Connor Lab, GalaxyProject SARS-CoV-2, InSaFLU, nf-core viralrecon, CWL workflow SARS-CoV-2, V-Pipe, Test team

Web page: https://github.com/virtual-biohackathons/covid-19-bh20

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IBISBA Workflows

Workflows from the Industrial Biotechnology Innovation and Synthetic Biology Accelerator (IBISBA 1.0) project, which is funded by the European Union Horizon 2020 program INRAIA-02 under grant agreement 730976.

The workflows also appear on https://hub.ibisba.eu

Space: Independent Teams

Public web page: https://www.ibisba.eu

Organisms: Homo sapiens, SARS-CoV-2

EOSC-Life WP3

No description specified

Space: EOSC-Life

Public web page: Not specified

Organisms: Not specified

Test team

No description specified

Space: COVID-19 Biohackathon

Public web page: Not specified

Organisms: Not specified

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The University of Manchester

Country: United Kingdom

City: Manchester

Web page: https://ror.org/027m9bs27

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Ten simple rules for making a software tool workflow-ready

Specimen Data Refinery, FAIR Computational Workflows

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Abstract (Expand)

Workflows have become a core part of computational scientific analysis in recent years. Automated computational workflows multiply the power of researchers, potentially turning “hand-cranked” data …

Authors: Paul Brack, Peter Crowther, Stian Soiland-Reyes, Stuart Owen, Douglas Lowe, Alan R. Williams, Quentin Groom, Mathias Dillen, Frederik Coppens, Björn Grüning, Ignacio Eguinoa, Philip Ewels, Carole Goble

Date Published: 24th Mar 2022

Publication Type: Journal

DOI: 10.1371/journal.pcbi.1009823

Citation: PLoS Comput Biol 18(3):e1009823

Created: 25th Apr 2022 at 11:43, Last updated: 16th Jan 2023 at 13:34

Views: 556, Downloads: 0

Landscape Analysis for the Specimen Data Refinery

Specimen Data Refinery

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This report reviews the current state-of-the-art applied approaches on automated tools, services and workflows for extracting information from images of natural history specimens and their labels. We …

Authors: Stephanie Walton, Laurence Livermore, Olaf Bánki, Robert W. N. Cubey, Robyn Drinkwater, Markus Englund, Carole Goble, Quentin Groom, Christopher Kermorvant, Isabel Rey, Celia M Santos, Ben Scott, Alan Williams, Zhengzhe Wu

Date Published: 14th Aug 2020

Publication Type: Journal

DOI: 10.3897/rio.6.e57602

Citation: Walton S, Livermore L, Bánki O, Cubey RWN, Drinkwater R, Englund M, Goble C, Groom Q, Kermorvant C, Rey I, Santos CM, Scott B, Williams AR, Wu Z (2020) Landscape Analysis for the Specimen Data Refinery. Research Ideas and Outcomes 6: e57602. https://doi.org/10.3897/rio.6.e57602

Created: 8th Dec 2021 at 16:58, Last updated: 16th Jan 2023 at 13:34

Views: 1039, Downloads: 0

INSaFLU: an automated open web-based bioinformatics suite “from-reads” for influenza whole-genome-sequencing-based surveillance

InSaFLU

Abstract (Expand)

Background A new era of flu surveillance has already started based on the genetic characterization and exploration of influenza virus evolution at whole-genome scale. Although this has been prioritized …d by national and international health authorities, the demanded technological transition to whole-genome sequencing (WGS)-based flu surveillance has been particularly delayed by the lack of bioinformatics infrastructures and/or expertise to deal with primary next-generation sequencing (NGS) data. Results We developed and implemented INSaFLU (“INSide the FLU”), which is the first influenza-oriented bioinformatics free web-based suite that deals with primary NGS data (reads) towards the automatic generation of the output data that are actually the core first-line “genetic requests” for effective and timely influenza laboratory surveillance (e.g., type and sub-type, gene and whole-genome consensus sequences, variants’ annotation, alignments and phylogenetic trees). By handling NGS data collected from any amplicon-based schema, the implemented pipeline enables any laboratory to perform multi-step software intensive analyses in a user-friendly manner without previous advanced training in bioinformatics. INSaFLU gives access to user-restricted sample databases and projects management, being a transparent and flexible tool specifically designed to automatically update project outputs as more samples are uploaded. Data integration is thus cumulative and scalable, fitting the need for a continuous epidemiological surveillance during the flu epidemics. Multiple outputs are provided in nomenclature-stable and standardized formats that can be explored in situ or through multiple compatible downstream applications for fine-tuned data analysis. This platform additionally flags samples as “putative mixed infections” if the population admixture enrolls influenza viruses with clearly distinct genetic backgrounds, and enriches the traditional “consensus-based” influenza genetic characterization with relevant data on influenza sub-population diversification through a depth analysis of intra-patient minor variants. This dual approach is expected to strengthen our ability not only to detect the emergence of antigenic and drug resistance variants but also to decode alternative pathways of influenza evolution and to unveil intricate routes of transmission. Conclusions In summary, INSaFLU supplies public health laboratories and influenza researchers with an open “one size fits all” framework, potentiating the operationalization of a harmonized multi-country WGS-based surveillance for influenza virus.

Authors: Vítor Borges, Miguel Pinheiro, Pedro Pechirra, Raquel Guiomar, João Paulo Gomes

Date Published: 1st Dec 2018

Publication Type: InProceedings

DOI: 10.1186/s13073-018-0555-0

Citation: Genome Med 10(1)

Created: 8th Apr 2020 at 11:56, Last updated: 16th Jan 2023 at 13:34

Views: 1700, Downloads: 0

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