SlideShare a Scribd company logo
1 of 123
Download to read offline
Genomes on Rails
  has_many :sequences
Hello
➊
Previously

    ➋
Production

    ➌
 Process
➊ Previously
The human genome


   15 years to decode
     3 billion letters
$3 billion
$3 billion ++
Race for the prize
Open data
Open source
Perl
Lots of Perl
Lots of Perl
 ~4500 modules
Onwards!
40 species
Map evolutionary
     space
Compare genomes
compare species
Compare genomes
compare species
Compare genomes

 compa re indi viduals
More Perl
~1500 modules
Quantum leap!
1000 personal
  genomes
beyond 23andme
1000 personal
  genomes
Hypertension
Diabetes
Coronary heart disease
Bipolar disorder
Malaria
➋ Production
Register projects


Register samples


  Sample prep


  Sequencing


    Analysis
Change!
Flexible data capture
Virtual fields
Sample


   Name
  Organism
Concentration
class Sample < ActiveRecord::Base
  has_many :descriptors
  has_many :descriptor_values
end
Key value pairs
Faster than you’d think
Change!
V1               V2


   Sample          Sample


   Name             Name
  Organism        Organism
Concentration   Concentration
                   Origin
                Quality metric
Rationalize!
V1               V2


   Sample          Sample


   Name             Name
  Organism        Organism
Concentration   Concentration
                   Origin
                Quality metric
Mapping!
V1               V3


   Sample          Sample


   Name             Name
  Organism         Species
Concentration   Concentration
   Origin          Origin
                Quality metric
Pipeline management
Workflow

 Task 1        Task 2        Task 3

  Name          Name         Name
Operator     Serial number   Passed
Instrument        Kit
Throughput!
320Tb 450 CPU
320Tb 450 CPU   Archive
75   Tb
pilot study!
Multiple apps
Multiple instances
Loosely coupled
Loose coupling is hard
Deployment
Maintenance
Monitoring
Hard to maintain
  separation
Support novel science
Single code base
nginx reverse proxy
fairnginx
Mongrel
Fast deployment
Automate everything
Play well with others!



 Interoperability!
Legacy databases
RESTful services
Generate API stubs
SCALE!
Trillionics
2   X
150Tb per week
Over 6 months
More hardware
400 additional nodes
additional 360 Tb
Towards a
Virtual Institute
Lots of data
Lots of data, lots of
      people
Lots of data, lots of
people, lots of compute
Lots of data, lots of
people, lots of compute,
      lots of uses
Lots of data, lots of
 people, lots of compute,
lots of uses, lots and lots
   and lots and lots...
➌ Process
Concept Requirements Development   Product
takes too lon
                                   g
Concept Requirements Development       Product
takes too lon
                                    g
Concept Requirements Development        Product




       the se change
Plan                 Development




 REVIEW        Concept




What we need              Get ready
Focused
Project owner is key
Weekly releases
More flexible
Less time
Better transparency
Less software
Sequencing informatics
Thank you
GREENISGOOD.CO.UK

More Related Content

Similar to Genomes on Rails project management and analysis

Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeq
Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeqIntroducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeq
Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeqGolden Helix Inc
 
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsRare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsGolden Helix Inc
 
Cassava genome hub
Cassava genome hubCassava genome hub
Cassava genome hubCIAT
 
Services For Science April 2009
Services For Science April 2009Services For Science April 2009
Services For Science April 2009Ian Foster
 
2014 nicta-reproducibility
2014 nicta-reproducibility2014 nicta-reproducibility
2014 nicta-reproducibilityc.titus.brown
 
BioIT Europe 2010 - BioCatalogue
BioIT Europe 2010 - BioCatalogueBioIT Europe 2010 - BioCatalogue
BioIT Europe 2010 - BioCatalogueBioCatalogue
 
Sharing massive data analysis: from provenance to linked experiment reports
Sharing massive data analysis: from provenance to linked experiment reportsSharing massive data analysis: from provenance to linked experiment reports
Sharing massive data analysis: from provenance to linked experiment reportsGaignard Alban
 
Next generation sequencing & microarray-- Genotypic Technology
Next generation sequencing & microarray-- Genotypic TechnologyNext generation sequencing & microarray-- Genotypic Technology
Next generation sequencing & microarray-- Genotypic TechnologyGenotypic Technology
 
So you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisSo you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisUniversity of California, Davis
 
Utility HPC: Right Systems, Right Scale, Right Science
Utility HPC: Right Systems, Right Scale, Right ScienceUtility HPC: Right Systems, Right Scale, Right Science
Utility HPC: Right Systems, Right Scale, Right ScienceChef Software, Inc.
 
Zero ETL analytics with LLAP in Azure HDInsight
Zero ETL analytics with LLAP in Azure HDInsightZero ETL analytics with LLAP in Azure HDInsight
Zero ETL analytics with LLAP in Azure HDInsightAshish Thapliyal
 
BioThings API: Building a FAIR API Ecosystem for Biomedical Knowledge
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeBioThings API: Building a FAIR API Ecosystem for Biomedical Knowledge
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeChunlei Wu
 
Solr and Elasticsearch, a performance study
Solr and Elasticsearch, a performance studySolr and Elasticsearch, a performance study
Solr and Elasticsearch, a performance studyCharlie Hull
 
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...Golden Helix Inc
 
Beyond Transparency: Success & Lessons From tambisBoston2003
Beyond Transparency: Success & Lessons From tambisBoston2003Beyond Transparency: Success & Lessons From tambisBoston2003
Beyond Transparency: Success & Lessons From tambisBoston2003robertstevens65
 
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...Bonnie Hurwitz
 
Prometheus lightning talk (Devops Dublin March 2015)
Prometheus lightning talk (Devops Dublin March 2015)Prometheus lightning talk (Devops Dublin March 2015)
Prometheus lightning talk (Devops Dublin March 2015)Brian Brazil
 

Similar to Genomes on Rails project management and analysis (20)

Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeq
Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeqIntroducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeq
Introducing VSWarehouse - A Scalable Genetic Data Warehouse for VarSeq
 
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Rare Variant Analysis Workflows: Analyzing NGS Data in Large CohortsRare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
Rare Variant Analysis Workflows: Analyzing NGS Data in Large Cohorts
 
Cassava genome hub
Cassava genome hubCassava genome hub
Cassava genome hub
 
Services For Science April 2009
Services For Science April 2009Services For Science April 2009
Services For Science April 2009
 
2014 nicta-reproducibility
2014 nicta-reproducibility2014 nicta-reproducibility
2014 nicta-reproducibility
 
BioIT Europe 2010 - BioCatalogue
BioIT Europe 2010 - BioCatalogueBioIT Europe 2010 - BioCatalogue
BioIT Europe 2010 - BioCatalogue
 
Sharing massive data analysis: from provenance to linked experiment reports
Sharing massive data analysis: from provenance to linked experiment reportsSharing massive data analysis: from provenance to linked experiment reports
Sharing massive data analysis: from provenance to linked experiment reports
 
DCC Keynote 2007
DCC Keynote 2007DCC Keynote 2007
DCC Keynote 2007
 
Next generation sequencing & microarray-- Genotypic Technology
Next generation sequencing & microarray-- Genotypic TechnologyNext generation sequencing & microarray-- Genotypic Technology
Next generation sequencing & microarray-- Genotypic Technology
 
Ngs part i 2013
Ngs part i 2013Ngs part i 2013
Ngs part i 2013
 
So you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisSo you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression Analysis
 
Utility HPC: Right Systems, Right Scale, Right Science
Utility HPC: Right Systems, Right Scale, Right ScienceUtility HPC: Right Systems, Right Scale, Right Science
Utility HPC: Right Systems, Right Scale, Right Science
 
Dr Justin Schonfeld - Bioinformatics Applications
Dr Justin Schonfeld - Bioinformatics ApplicationsDr Justin Schonfeld - Bioinformatics Applications
Dr Justin Schonfeld - Bioinformatics Applications
 
Zero ETL analytics with LLAP in Azure HDInsight
Zero ETL analytics with LLAP in Azure HDInsightZero ETL analytics with LLAP in Azure HDInsight
Zero ETL analytics with LLAP in Azure HDInsight
 
BioThings API: Building a FAIR API Ecosystem for Biomedical Knowledge
BioThings API: Building a FAIR API Ecosystem for Biomedical KnowledgeBioThings API: Building a FAIR API Ecosystem for Biomedical Knowledge
BioThings API: Building a FAIR API Ecosystem for Biomedical Knowledge
 
Solr and Elasticsearch, a performance study
Solr and Elasticsearch, a performance studySolr and Elasticsearch, a performance study
Solr and Elasticsearch, a performance study
 
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...
Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective ...
 
Beyond Transparency: Success & Lessons From tambisBoston2003
Beyond Transparency: Success & Lessons From tambisBoston2003Beyond Transparency: Success & Lessons From tambisBoston2003
Beyond Transparency: Success & Lessons From tambisBoston2003
 
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...
iMicrobe and iVirus: Extending the iPlant cyberinfrastructure from plants to ...
 
Prometheus lightning talk (Devops Dublin March 2015)
Prometheus lightning talk (Devops Dublin March 2015)Prometheus lightning talk (Devops Dublin March 2015)
Prometheus lightning talk (Devops Dublin March 2015)
 

More from Matt Wood

Genomics in the Cloud
Genomics in the CloudGenomics in the Cloud
Genomics in the CloudMatt Wood
 
How to make Friendfeeds and influence people
How to make Friendfeeds and influence peopleHow to make Friendfeeds and influence people
How to make Friendfeeds and influence peopleMatt Wood
 
Genomes On Rails
Genomes On RailsGenomes On Rails
Genomes On RailsMatt Wood
 
Into The Wonderful
Into The WonderfulInto The Wonderful
Into The WonderfulMatt Wood
 
Extreme Informatics
Extreme InformaticsExtreme Informatics
Extreme InformaticsMatt Wood
 
What can Bioinformaticians learn from YouTube?
What can Bioinformaticians learn from YouTube?What can Bioinformaticians learn from YouTube?
What can Bioinformaticians learn from YouTube?Matt Wood
 
The A to Z of developing for the web
The A to Z of developing for the webThe A to Z of developing for the web
The A to Z of developing for the webMatt Wood
 
Introduction to Scrum
Introduction to ScrumIntroduction to Scrum
Introduction to ScrumMatt Wood
 
30 Minutes With Rails
30 Minutes With Rails30 Minutes With Rails
30 Minutes With RailsMatt Wood
 
Subversion Best Practices
Subversion Best PracticesSubversion Best Practices
Subversion Best PracticesMatt Wood
 
Introduction to the Semantic Web
Introduction to the Semantic WebIntroduction to the Semantic Web
Introduction to the Semantic WebMatt Wood
 

More from Matt Wood (12)

Genomics in the Cloud
Genomics in the CloudGenomics in the Cloud
Genomics in the Cloud
 
How to make Friendfeeds and influence people
How to make Friendfeeds and influence peopleHow to make Friendfeeds and influence people
How to make Friendfeeds and influence people
 
Genomes On Rails
Genomes On RailsGenomes On Rails
Genomes On Rails
 
Into The Wonderful
Into The WonderfulInto The Wonderful
Into The Wonderful
 
Extreme Informatics
Extreme InformaticsExtreme Informatics
Extreme Informatics
 
What can Bioinformaticians learn from YouTube?
What can Bioinformaticians learn from YouTube?What can Bioinformaticians learn from YouTube?
What can Bioinformaticians learn from YouTube?
 
The A to Z of developing for the web
The A to Z of developing for the webThe A to Z of developing for the web
The A to Z of developing for the web
 
Introduction to Scrum
Introduction to ScrumIntroduction to Scrum
Introduction to Scrum
 
30 Minutes With Rails
30 Minutes With Rails30 Minutes With Rails
30 Minutes With Rails
 
Subversion Best Practices
Subversion Best PracticesSubversion Best Practices
Subversion Best Practices
 
Lucene
LuceneLucene
Lucene
 
Introduction to the Semantic Web
Introduction to the Semantic WebIntroduction to the Semantic Web
Introduction to the Semantic Web
 

Recently uploaded

"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenHervé Boutemy
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clashcharlottematthew16
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupFlorian Wilhelm
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostZilliz
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 

Recently uploaded (20)

"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
DevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache MavenDevoxxFR 2024 Reproducible Builds with Apache Maven
DevoxxFR 2024 Reproducible Builds with Apache Maven
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
Powerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time ClashPowerpoint exploring the locations used in television show Time Clash
Powerpoint exploring the locations used in television show Time Clash
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Streamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project SetupStreamlining Python Development: A Guide to a Modern Project Setup
Streamlining Python Development: A Guide to a Modern Project Setup
 
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage CostLeverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
Leverage Zilliz Serverless - Up to 50X Saving for Your Vector Storage Cost
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 

Genomes on Rails project management and analysis