SlideShare a Scribd company logo

Folker Meyer: Metagenomic Data Annotation

•Download as PPT, PDF•
•
GigaScience, BGI Hong Kong
GigaScience, BGI Hong Kong

Folker Meyer's talk from the 1st Earth Microbiome Project meeting in Shenzen.

Technology
1 of 24
Folker Meyer Argonne National Laboratory and University of Chicago June 14 th , 1 st EMP meeting Shenzhen, China Metagenome Annotation
Metagenomics needs the magic wand.. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],data Who are they? What are they doing?
Portals help with computational analysis ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
2010 state of metagenomics ,[object Object],[object Object],[object Object],[object Object]
2011: many small scale projects V3 03/2011 ,[object Object],[object Object],[object Object]
Even data upload is hard!  Jumploader Thanks to Rob Knight ’s team to pointing us there 
Part of an emerging digital biology ,[object Object],Source: MG-RAST, 800+ shared metagenomes
Computing cost dominate ,[object Object],Source: Rob Knight, UColorado From: Wilkening et al., IEEE Cluster09, 2009 computing sequencing
Challenges during shotgun metagenome analysis ,[object Object],[object Object],[object Object],[object Object]
Quality control for de-novo sequencing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Tell me if my data set is of type A or B ,[object Object],[object Object],Real data sets from MG-RAST ,[object Object],[object Object],K. Keegan, in preparation % duplicates varies also
Finding features ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Performance Analysis on simulated data sets w/ errors W. Trimble, in preparation
Characterizing features ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Presentation layer
MG-RAST v3 workflow (simplified) SFF, fastq and fasta data find emPCR and BridgePCR artifacts find coding regions/peptides using FragGeneScan (Ye, NAR 2010) Many databases integrated GSC’s M5nr Upload QC / normalization Similarities (Parallel Blat) Metabolic reconstruction Community reconstruction Metadata Feature prediction (FGS) Abundance profiles Metabolic model
The future ,[object Object],[object Object],[object Object],Source: Rob Knight, UColorado Driving force 600 GBp / run 60 GBp / run
Future 1: World is not clonal, study strain/species variation ,[object Object],new strain? new strain?
Future 2: Expand metadata (1): MIMS/MIMARKS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Capture metadata Extensive metadata questionnaire supporting offline editors // input
Expand metadata support (2): Capture metadata early Imagine adding metadata to the plot below: Very hard after the fact! capture metadata early Aanensen et al, Plos ONE, 2009
Many current challenges and pitfalls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Acknowledgements ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Thank you for your attention

Recommended

Machine Learning
Machine LearningMachine Learning
Machine LearningIndian Institute of Science Education and Research
 
Reconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsReconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsRutger Vos
 
Intro to metagenomic binning
Intro to metagenomic binningIntro to metagenomic binning
Intro to metagenomic binningA. Murat Eren
 
[2013.10.29] albertsen genomics metagenomics
[2013.10.29] albertsen genomics metagenomics[2013.10.29] albertsen genomics metagenomics
[2013.10.29] albertsen genomics metagenomicsMads Albertsen
 
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...Larry Smarr
 
Building an Information Infrastructure to Support Microbial Metagenomic Sciences
Building an Information Infrastructure to Support Microbial Metagenomic SciencesBuilding an Information Infrastructure to Support Microbial Metagenomic Sciences
Building an Information Infrastructure to Support Microbial Metagenomic SciencesLarry Smarr
 
Microbial Metagenomics Drives a New Cyberinfrastructure
Microbial Metagenomics Drives a New CyberinfrastructureMicrobial Metagenomics Drives a New Cyberinfrastructure
Microbial Metagenomics Drives a New CyberinfrastructureLarry Smarr
 
GLBIO/CCBC Metagenomics Workshop
GLBIO/CCBC Metagenomics WorkshopGLBIO/CCBC Metagenomics Workshop
GLBIO/CCBC Metagenomics WorkshopMorgan Langille
 

Recommended

Machine Learning
Machine LearningMachine Learning
Machine LearningIndian Institute of Science Education and Research
 
Reconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsReconstructing paleoenvironments using metagenomics
Reconstructing paleoenvironments using metagenomicsRutger Vos
 
Intro to metagenomic binning
Intro to metagenomic binningIntro to metagenomic binning
Intro to metagenomic binningA. Murat Eren
 
[2013.10.29] albertsen genomics metagenomics
[2013.10.29] albertsen genomics metagenomics[2013.10.29] albertsen genomics metagenomics
[2013.10.29] albertsen genomics metagenomicsMads Albertsen
 
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...
Building a Community Cyberinfrastructure to Support Marine Microbial Ecology ...Larry Smarr
 
Building an Information Infrastructure to Support Microbial Metagenomic Sciences
Building an Information Infrastructure to Support Microbial Metagenomic SciencesBuilding an Information Infrastructure to Support Microbial Metagenomic Sciences
Building an Information Infrastructure to Support Microbial Metagenomic SciencesLarry Smarr
 
Microbial Metagenomics Drives a New Cyberinfrastructure
Microbial Metagenomics Drives a New CyberinfrastructureMicrobial Metagenomics Drives a New Cyberinfrastructure
Microbial Metagenomics Drives a New CyberinfrastructureLarry Smarr
 
GLBIO/CCBC Metagenomics Workshop
GLBIO/CCBC Metagenomics WorkshopGLBIO/CCBC Metagenomics Workshop
GLBIO/CCBC Metagenomics WorkshopMorgan Langille
 
CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008Saul Kravitz
 
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...Larry Smarr
 
Introduction to 16S Microbiome Analysis
Introduction to 16S Microbiome AnalysisIntroduction to 16S Microbiome Analysis
Introduction to 16S Microbiome AnalysisBioinformatics and Computational Biosciences Branch
 
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics Christopher Mason
 
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.jennomics
 
Reframing Phylogenomics
Reframing PhylogenomicsReframing Phylogenomics
Reframing PhylogenomicsJoe Parker
 
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013VHIR Vall d’Hebron Institut de Recerca
 
Metagenomics sequencing
Metagenomics sequencingMetagenomics sequencing
Metagenomics sequencingcdgenomics525
 
2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorial2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorialc.titus.brown
 
Next Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and OpportunitiesNext Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and OpportunitiesChung-Tsai Su
 
CCBC tutorial beiko
CCBC tutorial beikoCCBC tutorial beiko
CCBC tutorial beikobeiko
 
Building bioinformatics resources for the global community
Building bioinformatics resources for the global communityBuilding bioinformatics resources for the global community
Building bioinformatics resources for the global communityExternalEvents
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsmikaelhuss
 
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesTools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
 
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016Prof. Wim Van Criekinge
 
Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Sijo A
 
Metagenomic analysis
Metagenomic analysisMetagenomic analysis
Metagenomic analysisAnimesh Kumar
 
Big data nebraska
Big data nebraskaBig data nebraska
Big data nebraskaAdina Chuang Howe
 
Advancing the Metagenomics Revolution
Advancing the Metagenomics RevolutionAdvancing the Metagenomics Revolution
Advancing the Metagenomics RevolutionLarry Smarr
 
Genomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel WeitschekGenomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel WeitschekData Driven Innovation
 
Integrative information management for systems biology
Integrative information management for systems biologyIntegrative information management for systems biology
Integrative information management for systems biologyNeil Swainston
 
Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Manuel Martín
 

More Related Content

What's hot

CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008Saul Kravitz
 
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...Larry Smarr
 
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics Christopher Mason
 
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.jennomics
 
Reframing Phylogenomics
Reframing PhylogenomicsReframing Phylogenomics
Reframing PhylogenomicsJoe Parker
 
Metagenomics sequencing
Metagenomics sequencingMetagenomics sequencing
Metagenomics sequencingcdgenomics525
 
2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorial2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorialc.titus.brown
 
Next Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and OpportunitiesNext Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and OpportunitiesChung-Tsai Su
 
CCBC tutorial beiko
CCBC tutorial beikoCCBC tutorial beiko
CCBC tutorial beikobeiko
 
Building bioinformatics resources for the global community
Building bioinformatics resources for the global communityBuilding bioinformatics resources for the global community
Building bioinformatics resources for the global communityExternalEvents
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsmikaelhuss
 
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesTools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
 
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016Prof. Wim Van Criekinge
 
Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Sijo A
 
Metagenomic analysis
Metagenomic analysisMetagenomic analysis
Metagenomic analysisAnimesh Kumar
 
Advancing the Metagenomics Revolution
Advancing the Metagenomics RevolutionAdvancing the Metagenomics Revolution
Advancing the Metagenomics RevolutionLarry Smarr
 
Genomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel WeitschekGenomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel WeitschekData Driven Innovation
 

What's hot (20)

CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008CAMERA Presentation at KNAW ICoMM Colloquium May 2008
CAMERA Presentation at KNAW ICoMM Colloquium May 2008
 
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
The OptIPlanet Collaboratory Supporting Microbial Metagenomics Researchers Wo...
 
Introduction to 16S Microbiome Analysis
Introduction to 16S Microbiome AnalysisIntroduction to 16S Microbiome Analysis
Introduction to 16S Microbiome Analysis
 
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
Cross-Kingdom Standards in Genomics, Epigenomics and Metagenomics
 
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
Microbiome studies using 16S ribosomal DNA PCR: some cautionary tales.
 
Reframing Phylogenomics
Reframing PhylogenomicsReframing Phylogenomics
Reframing Phylogenomics
 
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013
Introduction to Metagenomics Data Analysis - UEB-VHIR - 2013
 
Metagenomics sequencing
Metagenomics sequencingMetagenomics sequencing
Metagenomics sequencing
 
2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorial2015 beacon-metagenome-tutorial
2015 beacon-metagenome-tutorial
 
Next Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and OpportunitiesNext Generation Sequencing Informatics - Challenges and Opportunities
Next Generation Sequencing Informatics - Challenges and Opportunities
 
CCBC tutorial beiko
CCBC tutorial beikoCCBC tutorial beiko
CCBC tutorial beiko
 
Building bioinformatics resources for the global community
Building bioinformatics resources for the global communityBuilding bioinformatics resources for the global community
Building bioinformatics resources for the global community
 
Data analysis & integration challenges in genomics
Data analysis & integration challenges in genomicsData analysis & integration challenges in genomics
Data analysis & integration challenges in genomics
 
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesTools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
 
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
Galaxy dna-seq-variant calling-presentationandpractical_gent_april-2016
 
Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)Bioinformatics (Exam point of view)
Bioinformatics (Exam point of view)
 
Metagenomic analysis
Metagenomic analysisMetagenomic analysis
Metagenomic analysis
 
Big data nebraska
Big data nebraskaBig data nebraska
Big data nebraska
 
Advancing the Metagenomics Revolution
Advancing the Metagenomics RevolutionAdvancing the Metagenomics Revolution
Advancing the Metagenomics Revolution
 
Genomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel WeitschekGenomic Big Data Management, Integration and Mining - Emanuel Weitschek
Genomic Big Data Management, Integration and Mining - Emanuel Weitschek
 

Similar to Folker Meyer: Metagenomic Data Annotation

Integrative information management for systems biology
Integrative information management for systems biologyIntegrative information management for systems biology
Integrative information management for systems biologyNeil Swainston
 
Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Manuel Martín
 
Cool Informatics Tools and Services for Biomedical Research
Cool Informatics Tools and Services for Biomedical ResearchCool Informatics Tools and Services for Biomedical Research
Cool Informatics Tools and Services for Biomedical ResearchDavid Ruau
 
Bioinformatics_1_ChenS.pptx
Bioinformatics_1_ChenS.pptxBioinformatics_1_ChenS.pptx
Bioinformatics_1_ChenS.pptxxRowlet
 
Computation and Knowledge
Computation and KnowledgeComputation and Knowledge
Computation and KnowledgeIan Foster
 
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...GenomeInABottle
 
Jeff Grethe: CAMERA
Jeff Grethe: CAMERAJeff Grethe: CAMERA
Jeff Grethe: CAMERAIddo
 
The Status of ML Algorithms for Structure-property Relationships Using Matb...
The Status of ML Algorithms for Structure-property Relationships Using Matb...The Status of ML Algorithms for Structure-property Relationships Using Matb...
The Status of ML Algorithms for Structure-property Relationships Using Matb...Anubhav Jain
 
QconCat: From Instrument To Browser
QconCat: From Instrument To BrowserQconCat: From Instrument To Browser
QconCat: From Instrument To BrowserNeil Swainston
 
Big data at experimental facilities
Big data at experimental facilitiesBig data at experimental facilities
Big data at experimental facilitiesIan Foster
 
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
 
[2017-05-29] DNASmartTagger
[2017-05-29] DNASmartTagger [2017-05-29] DNASmartTagger
[2017-05-29] DNASmartTagger Eli Kaminuma
 
Metabolomic Data Analysis Workshop and Tutorials (2014)
Metabolomic Data Analysis Workshop and Tutorials (2014)Metabolomic Data Analysis Workshop and Tutorials (2014)
Metabolomic Data Analysis Workshop and Tutorials (2014)Dmitry Grapov
 
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817Ben Busby
 
Repeatable plant pathology bioinformatic analysis: Not everything is NGS data
Repeatable plant pathology bioinformatic analysis: Not everything is NGS dataRepeatable plant pathology bioinformatic analysis: Not everything is NGS data
Repeatable plant pathology bioinformatic analysis: Not everything is NGS dataLeighton Pritchard
 
Services For Science April 2009
Services For Science April 2009Services For Science April 2009
Services For Science April 2009Ian Foster
 
Ijricit 01-002 enhanced replica detection in short time for large data sets
Ijricit 01-002 enhanced replica detection in short time for large data setsIjricit 01-002 enhanced replica detection in short time for large data sets
Ijricit 01-002 enhanced replica detection in short time for large data setsIjripublishers Ijri
 
WikiPathways: how open source and open data can make omics technology more us...
WikiPathways: how open source and open data can make omics technology more us...WikiPathways: how open source and open data can make omics technology more us...
WikiPathways: how open source and open data can make omics technology more us...Chris Evelo
 

Similar to Folker Meyer: Metagenomic Data Annotation (20)

Integrative information management for systems biology
Integrative information management for systems biologyIntegrative information management for systems biology
Integrative information management for systems biology
 
Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?Automating Machine Learning - Is it feasible?
Automating Machine Learning - Is it feasible?
 
Cool Informatics Tools and Services for Biomedical Research
Cool Informatics Tools and Services for Biomedical ResearchCool Informatics Tools and Services for Biomedical Research
Cool Informatics Tools and Services for Biomedical Research
 
Bioinformatics_1_ChenS.pptx
Bioinformatics_1_ChenS.pptxBioinformatics_1_ChenS.pptx
Bioinformatics_1_ChenS.pptx
 
Computation and Knowledge
Computation and KnowledgeComputation and Knowledge
Computation and Knowledge
 
Cloud bioinformatics 2
Cloud bioinformatics 2Cloud bioinformatics 2
Cloud bioinformatics 2
 
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...
Genome in a Bottle - Towards new benchmarks for the “dark matter” of the huma...
 
Jeff Grethe: CAMERA
Jeff Grethe: CAMERAJeff Grethe: CAMERA
Jeff Grethe: CAMERA
 
The Status of ML Algorithms for Structure-property Relationships Using Matb...
The Status of ML Algorithms for Structure-property Relationships Using Matb...The Status of ML Algorithms for Structure-property Relationships Using Matb...
The Status of ML Algorithms for Structure-property Relationships Using Matb...
 
QconCat: From Instrument To Browser
QconCat: From Instrument To BrowserQconCat: From Instrument To Browser
QconCat: From Instrument To Browser
 
Big data at experimental facilities
Big data at experimental facilitiesBig data at experimental facilities
Big data at experimental facilities
 
Eccmid meet the expert 2015
Eccmid meet the expert 2015Eccmid meet the expert 2015
Eccmid meet the expert 2015
 
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
 
[2017-05-29] DNASmartTagger
[2017-05-29] DNASmartTagger [2017-05-29] DNASmartTagger
[2017-05-29] DNASmartTagger
 
Metabolomic Data Analysis Workshop and Tutorials (2014)
Metabolomic Data Analysis Workshop and Tutorials (2014)Metabolomic Data Analysis Workshop and Tutorials (2014)
Metabolomic Data Analysis Workshop and Tutorials (2014)
 
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817
Datasets and tools_from_ncbi_and_elsewhere_for_microbiome_research_v_62817
 
Repeatable plant pathology bioinformatic analysis: Not everything is NGS data
Repeatable plant pathology bioinformatic analysis: Not everything is NGS dataRepeatable plant pathology bioinformatic analysis: Not everything is NGS data
Repeatable plant pathology bioinformatic analysis: Not everything is NGS data
 
Services For Science April 2009
Services For Science April 2009Services For Science April 2009
Services For Science April 2009
 
Ijricit 01-002 enhanced replica detection in short time for large data sets
Ijricit 01-002 enhanced replica detection in short time for large data setsIjricit 01-002 enhanced replica detection in short time for large data sets
Ijricit 01-002 enhanced replica detection in short time for large data sets
 
WikiPathways: how open source and open data can make omics technology more us...
WikiPathways: how open source and open data can make omics technology more us...WikiPathways: how open source and open data can make omics technology more us...
WikiPathways: how open source and open data can make omics technology more us...
 

More from GigaScience, BGI Hong Kong

IDW2022: A decades experiences in transparent and interactive publication of ...
IDW2022: A decades experiences in transparent and interactive publication of ...IDW2022: A decades experiences in transparent and interactive publication of ...
IDW2022: A decades experiences in transparent and interactive publication of ...GigaScience, BGI Hong Kong
 
Scott Edmunds: Preparing a data paper for GigaByte
Scott Edmunds: Preparing a data paper for GigaByteScott Edmunds: Preparing a data paper for GigaByte
Scott Edmunds: Preparing a data paper for GigaByteGigaScience, BGI Hong Kong
 
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...STM Week: Demonstrating bringing publications to life via an End-to-end XML p...
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...GigaScience, BGI Hong Kong
 
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...GigaScience, BGI Hong Kong
 
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...GigaScience, BGI Hong Kong
 
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...GigaScience, BGI Hong Kong
 
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...GigaScience, BGI Hong Kong
 
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...GigaScience, BGI Hong Kong
 
Democratising biodiversity and genomics research: open and citizen science to...
Democratising biodiversity and genomics research: open and citizen science to...Democratising biodiversity and genomics research: open and citizen science to...
Democratising biodiversity and genomics research: open and citizen science to...GigaScience, BGI Hong Kong
 
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU Guix
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU GuixRicardo Wurmus: Reproducible genomics analysis pipelines with GNU Guix
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU GuixGigaScience, BGI Hong Kong
 
Anil Thanki at #ICG13: Aequatus: An open-source homology browser
Anil Thanki at #ICG13: Aequatus: An open-source homology browserAnil Thanki at #ICG13: Aequatus: An open-source homology browser
Anil Thanki at #ICG13: Aequatus: An open-source homology browserGigaScience, BGI Hong Kong
 
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...GigaScience, BGI Hong Kong
 
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant science
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant scienceVenice Juanillas at #ICG13: Rice Galaxy: an open resource for plant science
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant scienceGigaScience, BGI Hong Kong
 
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...GigaScience, BGI Hong Kong
 
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...GigaScience, BGI Hong Kong
 
Chris Armit at IDW2018: Democratising Data Publishing: A Global Perspective
Chris Armit at IDW2018: Democratising Data Publishing: A Global PerspectiveChris Armit at IDW2018: Democratising Data Publishing: A Global Perspective
Chris Armit at IDW2018: Democratising Data Publishing: A Global PerspectiveGigaScience, BGI Hong Kong
 
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...GigaScience, BGI Hong Kong
 
Reproducible method and benchmarking publishing for the data (and evidence) d...
Reproducible method and benchmarking publishing for the data (and evidence) d...Reproducible method and benchmarking publishing for the data (and evidence) d...
Reproducible method and benchmarking publishing for the data (and evidence) d...GigaScience, BGI Hong Kong
 
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...GigaScience, BGI Hong Kong
 

More from GigaScience, BGI Hong Kong (20)

IDW2022: A decades experiences in transparent and interactive publication of ...
IDW2022: A decades experiences in transparent and interactive publication of ...IDW2022: A decades experiences in transparent and interactive publication of ...
IDW2022: A decades experiences in transparent and interactive publication of ...
 
Scott Edmunds: Preparing a data paper for GigaByte
Scott Edmunds: Preparing a data paper for GigaByteScott Edmunds: Preparing a data paper for GigaByte
Scott Edmunds: Preparing a data paper for GigaByte
 
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...STM Week: Demonstrating bringing publications to life via an End-to-end XML p...
STM Week: Demonstrating bringing publications to life via an End-to-end XML p...
 
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...
Measuring richness. A RCT to quantify the benefits of metadata quality; Scott...
 
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...
Scott Edmunds: A new publishing workflow for rapid dissemination of genomes u...
 
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...
Scott Edmunds: Quantifying how FAIR is Hong Kong: The Hong Kong Shareability ...
 
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...
Scott Edmunds talk at IARC: How can we make science more trustworthy and FAIR...
 
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...
PAGAsia19 - The Digitalization of Ruili Botanical Garden Project: Production...
 
Democratising biodiversity and genomics research: open and citizen science to...
Democratising biodiversity and genomics research: open and citizen science to...Democratising biodiversity and genomics research: open and citizen science to...
Democratising biodiversity and genomics research: open and citizen science to...
 
Hong Kong Open Access & GigaScience: CCHK@10
Hong Kong Open Access & GigaScience: CCHK@10Hong Kong Open Access & GigaScience: CCHK@10
Hong Kong Open Access & GigaScience: CCHK@10
 
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU Guix
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU GuixRicardo Wurmus: Reproducible genomics analysis pipelines with GNU Guix
Ricardo Wurmus: Reproducible genomics analysis pipelines with GNU Guix
 
Anil Thanki at #ICG13: Aequatus: An open-source homology browser
Anil Thanki at #ICG13: Aequatus: An open-source homology browserAnil Thanki at #ICG13: Aequatus: An open-source homology browser
Anil Thanki at #ICG13: Aequatus: An open-source homology browser
 
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...
Paul Pavlidis at #ICG13: Monitoring changes in the Gene Ontology and their im...
 
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant science
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant scienceVenice Juanillas at #ICG13: Rice Galaxy: an open resource for plant science
Venice Juanillas at #ICG13: Rice Galaxy: an open resource for plant science
 
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...
Stefan Prost at #ICG13: Genome analyses show strong selection on coloration, ...
 
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...
Lisa Johnson at #ICG13: Re-assembly, quality evaluation, and annotation of 67...
 
Chris Armit at IDW2018: Democratising Data Publishing: A Global Perspective
Chris Armit at IDW2018: Democratising Data Publishing: A Global PerspectiveChris Armit at IDW2018: Democratising Data Publishing: A Global Perspective
Chris Armit at IDW2018: Democratising Data Publishing: A Global Perspective
 
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...
EMBL OA Week: FAIR or unfair? Principled publishing for more Open & Democrati...
 
Reproducible method and benchmarking publishing for the data (and evidence) d...
Reproducible method and benchmarking publishing for the data (and evidence) d...Reproducible method and benchmarking publishing for the data (and evidence) d...
Reproducible method and benchmarking publishing for the data (and evidence) d...
 
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...
Mary Ann Tuli: What MODs can learn from Journals – a GigaDB curator’s perspec...
 

Recently uploaded

How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Paola De la Torre
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...Martijn de Jong
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024The Digital Insurer
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure servicePooja Nehwal
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 

Recently uploaded (20)

How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101Salesforce Community Group Quito, Salesforce 101
Salesforce Community Group Quito, Salesforce 101
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘🐬 The future of MySQL is Postgres 🐘
🐬 The future of MySQL is Postgres 🐘
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure serviceWhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
WhatsApp 9892124323 ✓Call Girls In Kalyan ( Mumbai ) secure service
 
A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 

Folker Meyer: Metagenomic Data Annotation

  • 1. Folker Meyer Argonne National Laboratory and University of Chicago June 14 th , 1 st EMP meeting Shenzhen, China Metagenome Annotation
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. Even data upload is hard!  Jumploader Thanks to Rob Knight ’s team to pointing us there 
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13. Performance Analysis on simulated data sets w/ errors W. Trimble, in preparation
  • 14.
  • 16. MG-RAST v3 workflow (simplified) SFF, fastq and fasta data find emPCR and BridgePCR artifacts find coding regions/peptides using FragGeneScan (Ye, NAR 2010) Many databases integrated GSC’s M5nr Upload QC / normalization Similarities (Parallel Blat) Metabolic reconstruction Community reconstruction Metadata Feature prediction (FGS) Abundance profiles Metabolic model
  • 17.
  • 18.
  • 19.
  • 20. Expand metadata support (2): Capture metadata early Imagine adding metadata to the plot below: Very hard after the fact! capture metadata early Aanensen et al, Plos ONE, 2009
  • 21.
  • 22.
  • 23.
  • 24. Thank you for your attention