The document discusses a training webinar about PRIDE and ProteomeXchange. It begins with instructions for participating in the webinar and an overview of data resources at EMBL-EBI. It then covers PRIDE's mission to archive proteomics data, the ProteomeXchange consortium for standardized data submission, and tools for submitting data to PRIDE including PRIDE Converter, PRIDE Inspector, and the ProteomeXchange submission tool.
This document discusses mass spectrometry informatics formats developed by the Proteomics Standards Initiative. It describes standard formats such as mzIdentML, mzQuantML, and mzTab that have been created for proteomics data as well as ongoing work to extend mzTab to support metabolomics and glycomics data. It also provides information on the current status and adoption of these standards by the proteomics community.
The document discusses PRIDE and ProteomeXchange, resources for sharing public proteomics datasets. It describes how PRIDE stores mass spectrometry-based proteomics data and supports data sharing in the field. It also outlines the ProteomeXchange consortium which aims to standardize data submission and dissemination between proteomics repositories, and how data can be submitted to PRIDE using tools that support standard file formats.
Proteomics and the "big data" trend: challenges and new possibilitites (Talk ...Juan Antonio Vizcaino
The document discusses the challenges and opportunities of big data in proteomics. It describes how proteomics data volumes are growing rapidly due to technological advances, creating both computational challenges for data analysis and opportunities to reuse large amounts of public data. The PRIDE Archive at EBI stores over 4,000 proteomics datasets and provides tools like PRIDE Inspector to help analyze and validate large datasets. However, challenges remain around data standardization, metadata completeness, and the need for greater computational infrastructure and expertise to fully leverage the large amounts of shared proteomics data.
The US EPA’s National Center for Computational Toxicology (NCCT) has been both measuring and aggregating data to support our research efforts for over a decade. We have delivered these data via a number of publicly accessible websites, so-called dashboards, to provide transparent access to the outputs of the center. Since the inception of our research, software projects technologies have changed dramatically, as have the expectations regarding the methods by which to access data. Our informatics efforts provide access to millions of dollars of high-throughput screening data available in open, downloadable formats, via web services and through a rich web interface. Similarly, we provide access to experimental and predicted data associated with ~760,000 substances to serve the environmental chemistry community, and open source code for predictive models. This presentation will provide an overview of the efforts of NCCT to provide transparent access to our research and data via our publications (and accompanying supplementary data), via our Open Data policies, and through our databases, software tools and web services. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
Text and Non-textual Objects: Seamless access for scientists
Uwe Rosemann (German National Library of Science and Technology (TIB), Germany)
The European High Level Expert Group on Scientific data has formulated the challenges for a scientific infrastructure to be reached by 2030: “Our vision is a scientific e-infrastructure that supports seamless access, use, re-use, and trust of data. In a sense, the physical and technical infrastructure becomes invisible and the data themselves become the infrastructure – a valuable asset, on which science, technology, the economy and society can advance”.
Here, “data” is not restricted to primary data but also includes all non-textual material (graphs, spectra, videos, 3D-objects etc.).
The German National Library of Science and Technology (TIB) has developed a concept for a national competence center for non-textual materials which is now founded by the German State and by the German Federal Countries. The center has to perform the task: developing solutions and services together with the scientific community to make such data available, citable, sharable and usable, including visual search tools and enhanced content-based retrieval.
With solutions such as DataCite and modular development for extraction, indexing and visual searching of new scientific metadata, TIB will accept the challenge. And will make all data accessible to its users fast, convenient and easy to use.
The paper shows what special tools are developed by TIB in the context of scientific AV-media, 3D-objects and research data.
ICIC 2013 Conference Proceedings Antony Williams Royal Society of ChemistryDr. Haxel Consult
The Big Data Challenges Associated with Building a National Data Repository for Chemistry
Antony Williams (Royal Society of Chemistry , USA)
At a time when the data explosion has simply been redefined as “Big”, the hurdles associated with building a subject-specific data repository for chemistry are daunting. Combining a multitude of non-standard data formats for chemicals, related properties, reactions, spectra etc., together with the confusion of licensing and embargoing, and providing for data exchange and integration with services and platforms external to the repository, the challenge is significant. This all at a time when semantic technologies are touted as the fundamental technology to enhance integration and discoverability. Funding agencies are demanding change, especially a change towards access to open data to parallel their expectations around Open Access publishing. The Royal Society of Chemistry has been funded by the Engineering and Physical Science Research of the UK to deliver a “chemical database service” for UK scientists. This presentation will provide an overview of the challenges associated with this project and our progress in delivering a chemistry repository capable of handling the complex data types associated with chemistry. The benefits of such a repository in terms of providing data to develop prediction models to further enable scientific discovery will be discussed and the potential impact on the future of scientific publishing will also be examined.
This document discusses mass spectrometry informatics formats developed by the Proteomics Standards Initiative. It describes standard formats such as mzIdentML, mzQuantML, and mzTab that have been created for proteomics data as well as ongoing work to extend mzTab to support metabolomics and glycomics data. It also provides information on the current status and adoption of these standards by the proteomics community.
The document discusses PRIDE and ProteomeXchange, resources for sharing public proteomics datasets. It describes how PRIDE stores mass spectrometry-based proteomics data and supports data sharing in the field. It also outlines the ProteomeXchange consortium which aims to standardize data submission and dissemination between proteomics repositories, and how data can be submitted to PRIDE using tools that support standard file formats.
Proteomics and the "big data" trend: challenges and new possibilitites (Talk ...Juan Antonio Vizcaino
The document discusses the challenges and opportunities of big data in proteomics. It describes how proteomics data volumes are growing rapidly due to technological advances, creating both computational challenges for data analysis and opportunities to reuse large amounts of public data. The PRIDE Archive at EBI stores over 4,000 proteomics datasets and provides tools like PRIDE Inspector to help analyze and validate large datasets. However, challenges remain around data standardization, metadata completeness, and the need for greater computational infrastructure and expertise to fully leverage the large amounts of shared proteomics data.
The US EPA’s National Center for Computational Toxicology (NCCT) has been both measuring and aggregating data to support our research efforts for over a decade. We have delivered these data via a number of publicly accessible websites, so-called dashboards, to provide transparent access to the outputs of the center. Since the inception of our research, software projects technologies have changed dramatically, as have the expectations regarding the methods by which to access data. Our informatics efforts provide access to millions of dollars of high-throughput screening data available in open, downloadable formats, via web services and through a rich web interface. Similarly, we provide access to experimental and predicted data associated with ~760,000 substances to serve the environmental chemistry community, and open source code for predictive models. This presentation will provide an overview of the efforts of NCCT to provide transparent access to our research and data via our publications (and accompanying supplementary data), via our Open Data policies, and through our databases, software tools and web services. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
Text and Non-textual Objects: Seamless access for scientists
Uwe Rosemann (German National Library of Science and Technology (TIB), Germany)
The European High Level Expert Group on Scientific data has formulated the challenges for a scientific infrastructure to be reached by 2030: “Our vision is a scientific e-infrastructure that supports seamless access, use, re-use, and trust of data. In a sense, the physical and technical infrastructure becomes invisible and the data themselves become the infrastructure – a valuable asset, on which science, technology, the economy and society can advance”.
Here, “data” is not restricted to primary data but also includes all non-textual material (graphs, spectra, videos, 3D-objects etc.).
The German National Library of Science and Technology (TIB) has developed a concept for a national competence center for non-textual materials which is now founded by the German State and by the German Federal Countries. The center has to perform the task: developing solutions and services together with the scientific community to make such data available, citable, sharable and usable, including visual search tools and enhanced content-based retrieval.
With solutions such as DataCite and modular development for extraction, indexing and visual searching of new scientific metadata, TIB will accept the challenge. And will make all data accessible to its users fast, convenient and easy to use.
The paper shows what special tools are developed by TIB in the context of scientific AV-media, 3D-objects and research data.
ICIC 2013 Conference Proceedings Antony Williams Royal Society of ChemistryDr. Haxel Consult
The Big Data Challenges Associated with Building a National Data Repository for Chemistry
Antony Williams (Royal Society of Chemistry , USA)
At a time when the data explosion has simply been redefined as “Big”, the hurdles associated with building a subject-specific data repository for chemistry are daunting. Combining a multitude of non-standard data formats for chemicals, related properties, reactions, spectra etc., together with the confusion of licensing and embargoing, and providing for data exchange and integration with services and platforms external to the repository, the challenge is significant. This all at a time when semantic technologies are touted as the fundamental technology to enhance integration and discoverability. Funding agencies are demanding change, especially a change towards access to open data to parallel their expectations around Open Access publishing. The Royal Society of Chemistry has been funded by the Engineering and Physical Science Research of the UK to deliver a “chemical database service” for UK scientists. This presentation will provide an overview of the challenges associated with this project and our progress in delivering a chemistry repository capable of handling the complex data types associated with chemistry. The benefits of such a repository in terms of providing data to develop prediction models to further enable scientific discovery will be discussed and the potential impact on the future of scientific publishing will also be examined.
Este documento describe un proyecto para fortalecer las razas criollas de maíz en María La Baja, Colombia como alternativa de seguridad alimentaria y desarrollo sostenible. El proyecto incluye actividades como encuentros con sabedores locales, recolección y preservación de semillas, siembra, cosecha y poscosecha de maíz criollo. El objetivo general es fortalecer la seguridad alimentaria en la región a través del cultivo de maíz criollo.
El documento describe un taller práctico sobre la implementación de enfoques innovadores en la enseñanza, incluyendo el aprendizaje invertido y la conceptualización, desarrollo y cierre de una lección sobre reportajes. Los estudiantes aprendieron sobre reportajes a través de videos y discusión en grupo, desarrollaron sus propios reportajes con asesoría del profesor, y compartieron los resultados en un blog.
Aprendizaje Vivencial: Modelo de aprendizaje que implica la vivencia de una experiencia en la que el alumno puede sentir o hacer cosas que fortalecen sus aprendizajes.
UPDATE 3!!! Here's the revise!
Creating Content with Little Doodle.
Join the adventure!
Creating Creative Content with Little Doodle in Space.
Little Doodle travels the Universe searching
for creatures. Creative content will excite your customers, let us create a creative for you.
At the end of the presentation, sign up for a chance to win Little Doodle original art.
Please share this slide, thank you.
http://www.erosner.com
http://www.theartpillow.com
must-See: Best Content Marketing Examples
rosner1@mac.com
Data diving: understanding reputation management for researchersKudos
As researchers take a more active approach to managing their reputation, what can the data generated by their activities tell us about the best ways to present research online? Many different parties across the scholarly communications community are seeking to understand the data in their respective systems, to determine cause and effect across a range of activities and outcomes. What pitfalls must be avoided, and how can we better integrate our efforts to maximize understanding of the tools to which researchers are turning to support career progression.
El programa Pueblos Mágicos de México, creado en 2001, designa a 111 pueblos que cumplen criterios relacionados con su arquitectura, historia y cultura. Aunque genera una alta derrama económica, también se ha asociado con un aumento de la inseguridad. El programa se ha vuelto popular y varios otros países latinoamericanos buscan implementar iniciativas similares para atraer turismo.
The document describes the design, implementation, and testing of a sediment-based microbial fuel cell to produce power. Key aspects included using crushed graphite for the anode buried in sediment with a free-floating cathode, and the design achieved an average power density of 1.07 watts/m3, meeting the goal of producing 1 watt/m3 of power within budget and timeline constraints. Testing included polarization curves and power density measurements over time to analyze the fuel cell's performance.
This document discusses various mechanisms for paying for dental care, including private fee-for-service, post-payment plans, and private third party prepayment plans such as commercial insurance companies and non-profit plans like Delta Dental. It also covers prepaid group practice plans, capitation plans, salaries, and public programs like Medicare and Medicaid. Key aspects of reimbursement for dentists and advantages and disadvantages of different payment mechanisms are described.
I'm sharing this PPT which I had presented in my university as a part of my assignments. This PPT can be helpful for students of psychology to prepare their notes. It is brief, covers major points of the topic. Hope people like it.
The Baltic Sea is surrounded by several Northern European countries and has attracted tourists for activities like boating and fishing. The Tatra Mountains form the highest range in the Carpathian Mountains along the Poland-Slovakia border. Visitors also come to enjoy forests, food and historic sites such as Teutonic knight castles and fortifications in the summer. Warsaw is Poland's capital and contains contrasts and surprises, while Krakow was formerly the country's capital and attracts visitors. The Polish flag depicts the national colors and Silesian noodles are a local food.
PRIDE is a proteomics database at EMBL-EBI that stores mass spectrometry-based proteomics data, including peptide and protein identifications and quantifications. It is part of the ProteomeXchange consortium, which aims to facilitate standardized data submission and dissemination between proteomics repositories. The document outlines the types of data stored in PRIDE, how to access and submit data, and tools for data conversion and visualization like PRIDE Converter 2 and PRIDE Inspector.
The document discusses proteomics repositories and their role in sharing mass spectrometry (MS) proteomics data. It describes the main types of information stored in MS proteomics repositories, including raw experimental data, identification and quantification results, metadata, and other associated information. The document outlines some of the main existing repositories, including PRIDE Archive, PeptideAtlas, and Global Proteome Machine, and whether they reprocess data through a standardized pipeline or store data as published. Reprocessing repositories provide an updated view of data through consistent analysis, while no-reprocessing repositories preserve the original analysis. Data sharing is important for independent review, meta-analysis, and advancing the field.
The document discusses PRIDE, a proteomics data repository at EMBL-EBI. It describes how PRIDE stores mass spectrometry proteomics data, its role within the ProteomeXchange consortium, and how researchers can submit data to PRIDE including the use of mzIdentML and PRIDE tools.
The document discusses data standards for proteomics, including those developed by the Proteomics Standards Initiative (PSI). It describes several existing PSI standards for mass spectrometry data, including mzML, mzIdentML, mzQuantML, and TraML. It provides an example of the successful mzML standard and discusses how mzIdentML has been widely adopted for representing peptide and protein identifications.
PRIDE resources and ProteomeXchange
- PRIDE is a proteomics data repository at EMBL-EBI that stores mass spectrometry-based proteomics data.
- It is part of the ProteomeXchange consortium, which provides a framework for standardized data submission and dissemination between proteomics repositories.
- This presentation discusses how to submit data to PRIDE/ProteomeXchange using PRIDE tools, including converting files to mzIdentML format and using the PX submission tool for metadata and file transfer.
PRIDE and ProteomeXchange: supporting the cultural change in proteomics publi...Juan Antonio Vizcaino
The document discusses PRIDE and ProteomeXchange, which are resources that support the deposition of proteomics data to public repositories. PRIDE stores mass spectrometry-based proteomics data, and is one of the repositories that is part of ProteomeXchange, a framework that allows standard submission of proteomics data between major repositories. The document outlines the cultural change in proteomics towards public data sharing, and provides information on submitting proteomics data to PRIDE and accessing data deposited in PRIDE and ProteomeXchange.
This document introduces several proteomics data standards developed by the Proteomics Standards Initiative (PSI), including mzML for mass spectrometry data, mzIdentML for peptide and protein identifications, mzQuantML for quantification data, and mzTab for final identification and quantification results. It describes how these standards address the need for data standardization in proteomics as the field has evolved. It also discusses how these standards have been implemented in proteomics databases, software tools, and data repositories like ProteomeXchange to facilitate data sharing and analysis.
Este documento describe un proyecto para fortalecer las razas criollas de maíz en María La Baja, Colombia como alternativa de seguridad alimentaria y desarrollo sostenible. El proyecto incluye actividades como encuentros con sabedores locales, recolección y preservación de semillas, siembra, cosecha y poscosecha de maíz criollo. El objetivo general es fortalecer la seguridad alimentaria en la región a través del cultivo de maíz criollo.
El documento describe un taller práctico sobre la implementación de enfoques innovadores en la enseñanza, incluyendo el aprendizaje invertido y la conceptualización, desarrollo y cierre de una lección sobre reportajes. Los estudiantes aprendieron sobre reportajes a través de videos y discusión en grupo, desarrollaron sus propios reportajes con asesoría del profesor, y compartieron los resultados en un blog.
Aprendizaje Vivencial: Modelo de aprendizaje que implica la vivencia de una experiencia en la que el alumno puede sentir o hacer cosas que fortalecen sus aprendizajes.
UPDATE 3!!! Here's the revise!
Creating Content with Little Doodle.
Join the adventure!
Creating Creative Content with Little Doodle in Space.
Little Doodle travels the Universe searching
for creatures. Creative content will excite your customers, let us create a creative for you.
At the end of the presentation, sign up for a chance to win Little Doodle original art.
Please share this slide, thank you.
http://www.erosner.com
http://www.theartpillow.com
must-See: Best Content Marketing Examples
rosner1@mac.com
Data diving: understanding reputation management for researchersKudos
As researchers take a more active approach to managing their reputation, what can the data generated by their activities tell us about the best ways to present research online? Many different parties across the scholarly communications community are seeking to understand the data in their respective systems, to determine cause and effect across a range of activities and outcomes. What pitfalls must be avoided, and how can we better integrate our efforts to maximize understanding of the tools to which researchers are turning to support career progression.
El programa Pueblos Mágicos de México, creado en 2001, designa a 111 pueblos que cumplen criterios relacionados con su arquitectura, historia y cultura. Aunque genera una alta derrama económica, también se ha asociado con un aumento de la inseguridad. El programa se ha vuelto popular y varios otros países latinoamericanos buscan implementar iniciativas similares para atraer turismo.
The document describes the design, implementation, and testing of a sediment-based microbial fuel cell to produce power. Key aspects included using crushed graphite for the anode buried in sediment with a free-floating cathode, and the design achieved an average power density of 1.07 watts/m3, meeting the goal of producing 1 watt/m3 of power within budget and timeline constraints. Testing included polarization curves and power density measurements over time to analyze the fuel cell's performance.
This document discusses various mechanisms for paying for dental care, including private fee-for-service, post-payment plans, and private third party prepayment plans such as commercial insurance companies and non-profit plans like Delta Dental. It also covers prepaid group practice plans, capitation plans, salaries, and public programs like Medicare and Medicaid. Key aspects of reimbursement for dentists and advantages and disadvantages of different payment mechanisms are described.
I'm sharing this PPT which I had presented in my university as a part of my assignments. This PPT can be helpful for students of psychology to prepare their notes. It is brief, covers major points of the topic. Hope people like it.
The Baltic Sea is surrounded by several Northern European countries and has attracted tourists for activities like boating and fishing. The Tatra Mountains form the highest range in the Carpathian Mountains along the Poland-Slovakia border. Visitors also come to enjoy forests, food and historic sites such as Teutonic knight castles and fortifications in the summer. Warsaw is Poland's capital and contains contrasts and surprises, while Krakow was formerly the country's capital and attracts visitors. The Polish flag depicts the national colors and Silesian noodles are a local food.
PRIDE is a proteomics database at EMBL-EBI that stores mass spectrometry-based proteomics data, including peptide and protein identifications and quantifications. It is part of the ProteomeXchange consortium, which aims to facilitate standardized data submission and dissemination between proteomics repositories. The document outlines the types of data stored in PRIDE, how to access and submit data, and tools for data conversion and visualization like PRIDE Converter 2 and PRIDE Inspector.
The document discusses proteomics repositories and their role in sharing mass spectrometry (MS) proteomics data. It describes the main types of information stored in MS proteomics repositories, including raw experimental data, identification and quantification results, metadata, and other associated information. The document outlines some of the main existing repositories, including PRIDE Archive, PeptideAtlas, and Global Proteome Machine, and whether they reprocess data through a standardized pipeline or store data as published. Reprocessing repositories provide an updated view of data through consistent analysis, while no-reprocessing repositories preserve the original analysis. Data sharing is important for independent review, meta-analysis, and advancing the field.
The document discusses PRIDE, a proteomics data repository at EMBL-EBI. It describes how PRIDE stores mass spectrometry proteomics data, its role within the ProteomeXchange consortium, and how researchers can submit data to PRIDE including the use of mzIdentML and PRIDE tools.
The document discusses data standards for proteomics, including those developed by the Proteomics Standards Initiative (PSI). It describes several existing PSI standards for mass spectrometry data, including mzML, mzIdentML, mzQuantML, and TraML. It provides an example of the successful mzML standard and discusses how mzIdentML has been widely adopted for representing peptide and protein identifications.
PRIDE resources and ProteomeXchange
- PRIDE is a proteomics data repository at EMBL-EBI that stores mass spectrometry-based proteomics data.
- It is part of the ProteomeXchange consortium, which provides a framework for standardized data submission and dissemination between proteomics repositories.
- This presentation discusses how to submit data to PRIDE/ProteomeXchange using PRIDE tools, including converting files to mzIdentML format and using the PX submission tool for metadata and file transfer.
PRIDE and ProteomeXchange: supporting the cultural change in proteomics publi...Juan Antonio Vizcaino
The document discusses PRIDE and ProteomeXchange, which are resources that support the deposition of proteomics data to public repositories. PRIDE stores mass spectrometry-based proteomics data, and is one of the repositories that is part of ProteomeXchange, a framework that allows standard submission of proteomics data between major repositories. The document outlines the cultural change in proteomics towards public data sharing, and provides information on submitting proteomics data to PRIDE and accessing data deposited in PRIDE and ProteomeXchange.
This document introduces several proteomics data standards developed by the Proteomics Standards Initiative (PSI), including mzML for mass spectrometry data, mzIdentML for peptide and protein identifications, mzQuantML for quantification data, and mzTab for final identification and quantification results. It describes how these standards address the need for data standardization in proteomics as the field has evolved. It also discusses how these standards have been implemented in proteomics databases, software tools, and data repositories like ProteomeXchange to facilitate data sharing and analysis.
ProteomeXchange: Update for the C-HPP Consortium.
10th C-HPP Workshop: “Proteome data management and identification of missing proteins".
Bangkok, Thailand. 09/08/2015. Remote presentation.
Mining the hidden proteome using hundreds of public proteomics datasetsJuan Antonio Vizcaino
The document discusses mining hidden proteomics data using public proteomics datasets. It describes how the PRIDE Cluster tool clusters over 250 million spectra from the PRIDE Archive, including over 190 million previously unidentified spectra. This clustering identified inconsistent clusters that could be reanalyzed, inferred identifications for 9.1 million originally unidentified spectra contained within reliable identification clusters, and consistently unidentified clusters that could be targeted for further analysis to identify unknown peptides. The clustering took 5 days on a 340-core system and generated 28 million clusters.
ELIXIR Pilot Actions launched in 2014: Integration of BILS-ProteomeXchange us...Juan Antonio Vizcaino
This is a report of the ELIXIR pilot project performed by the EMBL-EBI (PRIDE and System teams), BILS and EUDAT. The title of the pilot project was: "Integration of BILS-ProteomeXchange using EUDAT resources".
This document summarizes a presentation about proteomics repositories. It discusses why sharing proteomics data is important, the types of information stored in repositories, and some of the main existing repositories and their characteristics. Some repositories, like PRIDE and MassIVE, store data as originally analyzed without reprocessing. Others, like PeptideAtlas and GPMDB, reprocess raw data using a standardized pipeline to provide an updated view. The document also discusses resources developed from draft human proteome papers, including proteomicsDB and the Human Proteome Map.
PRIDE is a proteomics database that stores mass spectrometry-based proteomics data as part of the ProteomeXchange consortium. It contains identification and quantification data from peptide and protein expression analyses as well as post-translational modifications and mass spectra. Data is organized into datasets and assays and can be submitted to PRIDE via tools that export results into mzIdentML or mzTab format. Complete submissions contain identified spectra mapped to results, while partial submissions provide limited experimental details. PRIDE Inspector and the PX submission tool facilitate validation, visualization and submission of proteomics data to PRIDE.
The document discusses the activities of the EMBL-EBI ELIXIR Node related to proteomics data and analysis. It describes how EMBL-EBI contributes to the ELIXIR platforms of data, tools, interoperability, compute, and training through its work on the PRIDE Archive and ProteomeXchange repository, development of proteomics data standards and software tools, implementation of reproducible proteomics pipelines, and proteomics training courses. The PRIDE Archive contains over 280 terabytes of mass spectrometry proteomics data from over 51 countries and has seen rapid growth in recent years.
An overview of the PRIDE ecosystem of resources and computational tools for m...Juan Antonio Vizcaino
The document provides an overview of the PRIDE ecosystem of resources and computational tools for mass spectrometry proteomics data. It describes PRIDE Archive and ProteomeXchange as repositories for proteomics data, as well as tools like PRIDE Inspector for visualizing and validating data. It also discusses how public proteomics data is increasingly being reused, and added-value resources like PRIDE Cluster and PRIDE Proteomes that provide aggregated views of proteomics data.
An update of the activities of the ProteomeXchange Consortium of proteomics resources given at HUPO 2016 (Taipei). Some slides at the end of the presentation are from Nuno Bandeira.
Similar to PRIDE and ProteomeXchange: Training webinar (20)
Reusing and integrating public proteomics data to improve our knowledge of th...Juan Antonio Vizcaino
Dr. Juan Antonio Vizcaíno discusses reuse and integration of public proteomics data to improve knowledge of the human proteome. He describes how the PRIDE database stores mass spectrometry-based proteomics data and how ProteomeXchange provides a framework for data submission and dissemination between repositories. Reanalysis of public proteomics data is increasing and can be used for proteogenomics studies and meta-analyses to integrate proteomics and genomics data and better understand the human proteome.
This document provides an overview of proteomics data standards developed by the Proteomics Standards Initiative (PSI). It discusses the need for data standards, describes existing PSI standards like mzML for mass spectrometry data, mzIdentML for identification data, and mzTab for final results. The document also provides background on the development and adoption of these standards over time to support the evolving needs of the proteomics community.
Dr. Juan Antonio Vizcaíno presented on the reuse of public proteomics data. The submission of proteomics datasets to repositories like PRIDE has increased dramatically in recent years. Downloads and reuse of data from PRIDE has also grown significantly, reaching 295 terabytes in 2017. Common ways researchers reuse public proteomics data include verifying published results, building spectral libraries, finding interesting datasets to reanalyze for new discoveries, and benchmarking new algorithms. Data sharing allows information to be extracted and reused in new experiments, advancing protein knowledge in areas like UniProt and neXtProt databases.
1) There are several major proteomics repositories that serve different purposes, including repositories that store raw data without reprocessing it (PRIDE Archive, MassIVE, jPOST, iProx, PASSEL) and repositories that reprocess all raw data using standardized methods (PeptideAtlas, GPMDB, proteomicsDB, Human Proteome Map).
2) The document outlines the types of information commonly stored in proteomics repositories, including raw data, identification results, quantification, and metadata. It also discusses standards for file formats.
3) Data sharing in proteomics is becoming more important, driven by journals and funders, to enable reproducible science and maximize the value of research findings. Repositories support
Proteomics is the large-scale study of proteins. The document provides an overview of the history and concepts of proteomics, including definitions of key terms, descriptions of pioneering scientists and techniques, and the importance of bioinformatics in proteomics research. It discusses how proteomics has evolved from protein sequencing and gel electrophoresis to modern mass spectrometry-based techniques and quantitative analysis. The increasing role of proteomics in fields like structural biology and clinical applications is also noted.
ELIXIR Implementation Study: “Mining the Proteome: Enabling Automated Process...Juan Antonio Vizcaino
This document summarizes a webinar about developing open proteomics data analysis pipelines in the cloud. It discusses creating reusable workflows for common proteomics analysis tasks like identification, quantification, and quality control. These workflows would be deployed in cloud environments like the EMBL-EBI "Embassy Cloud" and connected to public proteomics databases like PRIDE. The goals are to make large-scale proteomics analysis more reproducible, scalable, and accessible to the community. An implementation study is underway to develop initial workflows for common analysis types, with plans to expand the available tools and optimize the pipelines for growing proteomics data volumes in the future.
This document provides an overview and status update of various proteomics data standards and related efforts from the PSI Proteome Informatics working group. It discusses the structure and timeline of developments for mzIdentML, mzQuantML, mzTab, and related proteogenomics formats. It also outlines plans for the meeting, including further developing mzTab for different applications and the new proVCF format for representing genetic variation at the protein level.
1) ProteomeXchange is a global database containing proteomics data from several repositories including PRIDE, MassIVE, and jPOST.
2) A new member, iProX, joined in 2017 and contains over 60 terabytes of data from China.
3) Usage of ProteomeXchange data is increasing, with PRIDE downloads growing from 50 terabytes in 2013 to over 295 terabytes in 2017.
Developing open data analysis pipelines in the cloud: Enabling the ‘big data’...Juan Antonio Vizcaino
Dr. Juan Antonio Vizcaíno presented on developing open data analysis pipelines in the cloud to enable large-scale analysis of proteomics data. He introduced PRIDE and ProteomeXchange as repositories for proteomics data that are seeing substantial growth. Moving analysis pipelines to the cloud will facilitate public reuse of large datasets, improve scalability, and ensure reproducibility. Initial pipelines have been created for identification, quantification, and quality control of mass spectrometry data and deployed on the EMBL-EBI cloud platform. Future work includes optimizing access to PRIDE data and developing pipelines for analysis of DIA and proteogenomics data.
The document discusses the ELIXIR Proteomics Community and its plans. It describes how 11 ELIXIR nodes support the community to develop sustainable proteomics tools and resources and make them FAIR. It highlights existing resources like the PRIDE database and ProteomeXchange repository. Future plans include developing proteoform-centric approaches, integrating omics data, and improving analysis workflows and data management.
This document summarizes Juan A. Vizcaíno's presentation on the ELIXIR Proteomics Community. It discusses the establishment of the community through an implementation study and strategy meeting. The community aims to develop standardized proteomics data analysis pipelines and deploy them in a cloud environment. It will also work to improve proteomics data standards and integrate proteomics with other omics data through activities like the Proteomics Standards Initiative. The ProteomeXchange database is a major resource overseen by the community for storing and sharing proteomics data internationally.
A proteomics data “gold mine” at your disposal: Now that the data is there, w...Juan Antonio Vizcaino
The document discusses the reuse of public proteomics data. It describes how data from the PRoteomics IDEntifications (PRIDE) Archive can be reanalyzed to conduct proteogenomics studies, discover new post-translational modifications and variants, and enable meta-analysis studies of protein-protein interactions and associations. It also examines challenges around analyzing the "dark proteome" of consistently unidentified spectra in public datasets and developing open analysis pipelines for proteomics data in cloud environments.
This document discusses the ProteomeXchange Consortium and recent updates. It provides statistics on data submissions and downloads. Over 7,475 datasets have been submitted from over 50 countries, with the majority from the US, Germany, and China. PRIDE and MassIVE are the largest repositories. A new prospective member, iProX, is described which will be the main proteomics data sharing platform in China. Guidelines are being developed to handle reprocessed datasets submitted to repositories.
Public proteomics data: a (mostly unexploited) gold mine for computational re...Juan Antonio Vizcaino
The document discusses public proteomics data available through the PRIDE Archive at the European Bioinformatics Institute. It provides statistics on data submissions and downloads, which continue to increase significantly each year. The author advocates for reusing public proteomics data through approaches like proteogenomics studies, discovery of new post-translational modifications, and meta-analysis studies. Spectrum clustering is presented as a method to further analyze and draw insights from large proteomics datasets.
This document discusses the reuse of public proteomics data. It provides statistics on proteomics datasets submitted to PRIDE, including the top submitting countries, types of submissions, data volume, and most studied species. It then discusses several ways that public proteomics data is being reused, including to verify published results, build spectral libraries, find new splice isoforms or post-translational modifications, benchmark new tools, and contribute to protein evidence in databases like UniProt. Specific examples of data reuse are also provided, such as for spectral searching, meta-analysis, and repurposing data for proteogenomics studies or discovering novel PTMs.
This document discusses proteomics repositories and data sharing in proteomics. It describes the types of information stored in MS proteomics repositories, including raw data, identification results, quantification, and metadata. It outlines several main repositories, distinguishing between those that do not reprocess data, like PRIDE and MassIVE, and those that do reprocess data through a standardized pipeline, like PeptideAtlas and GPMDB. It also discusses resources focused on drafts of the human proteome, such as proteomicsDB and the Human Proteome Map. Overall, the document provides an overview of existing proteomics repositories and issues around data sharing in the field.
The document introduces several proteomics data standards developed by the Proteomics Standards Initiative (PSI), including mzML, mzIdentML, mzQuantML, TraML, and mzTab. It provides an overview of each standard, describing what type of data it encodes (e.g. mass spectrometry data, identification data, quantification data), its timeline of development and versions, and its increasing adoption by proteomics software and databases. The document emphasizes that data standards are necessary for data sharing and integration in proteomics given the large number of experimental workflows and data types.
Proteomics is the large-scale study of proteins. It has become an important field due to developments in mass spectrometry and genomics. However, proteomics generates large amounts of complex data that requires bioinformatics analysis. The history of proteomics includes early pioneers in protein sequencing and mass spectrometry techniques. Current areas of focus include biomarker discovery, structural biology, and integrating proteomics with other omics data through systems biology approaches.
BREEDING METHODS FOR DISEASE RESISTANCE.pptxRASHMI M G
Plant breeding for disease resistance is a strategy to reduce crop losses caused by disease. Plants have an innate immune system that allows them to recognize pathogens and provide resistance. However, breeding for long-lasting resistance often involves combining multiple resistance genes
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...AbdullaAlAsif1
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
Remote Sensing and Computational, Evolutionary, Supercomputing, and Intellige...University of Maribor
Slides from talk:
Aleš Zamuda: Remote Sensing and Computational, Evolutionary, Supercomputing, and Intelligent Systems.
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Inter-Society Networking Panel GRSS/MTT-S/CIS Panel Session: Promoting Connection and Cooperation
https://www.etran.rs/2024/en/home-english/
Travis Hills' Endeavors in Minnesota: Fostering Environmental and Economic Pr...Travis Hills MN
Travis Hills of Minnesota developed a method to convert waste into high-value dry fertilizer, significantly enriching soil quality. By providing farmers with a valuable resource derived from waste, Travis Hills helps enhance farm profitability while promoting environmental stewardship. Travis Hills' sustainable practices lead to cost savings and increased revenue for farmers by improving resource efficiency and reducing waste.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Nucleophilic Addition of carbonyl compounds.pptxSSR02
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
3D Hybrid PIC simulation of the plasma expansion (ISSS-14)
PRIDE and ProteomeXchange: Training webinar
1. PRIDE and ProteomeXchange: Training
webinar
Dr. Juan Antonio Vizcaíno
PRIDE Group Coordinator
Proteomics Services Team
EMBL-EBI
Hinxton, Cambridge, UK
juan@ebi.ac.uk
2. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Welcome - webinar instructions
• Gototraining works best in Chrome or IE – avoid Firefox
due to audio issues with Macs.
• To access the full features of Gototraining, use the
desktop version by clicking “switch to desktop version”.
• All microphones will be muted whilst the trainer is
speaking.
• If you have a question during this time or at the end,
please use the chat box at the bottom of the
gototraining box.
• Please complete the feedback survey which will launch
at the end of the webinar.
3. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Data resources at EMBL-EBI
Genes, genomes & variation
RNA Central
Array
Express
Expression Atlas
Metabolights
PRIDE
InterPro Pfam UniProt
ChEMBL ChEBI
Molecular structures
Protein Data Bank in Europe
Electron Microscopy Data Bank
European Nucleotide Archive
European Variation Archive
European Genome-phenome Archive
Gene, protein & metabolite expression
Protein sequences, families & motifs
Chemical biology
Reactions, interactions &
pathways
IntAct Reactome MetaboLights
Systems
BioModels Enzyme Portal BioSamples
Ensembl
Ensembl Genomes
GWAS Catalog
Metagenomics portal
Europe PubMed Central
Gene Ontology
Experimental Factor
Ontology
Literature & ontologies
4. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Data resources at EMBL-EBI
Genes, genomes & variation
RNA Central
Array
Express
Expression Atlas
Metabolights
PRIDE
InterPro Pfam UniProt
ChEMBL ChEBI
Molecular structures
Protein Data Bank in Europe
Electron Microscopy Data Bank
European Nucleotide Archive
European Variation Archive
European Genome-phenome Archive
Gene, protein & metabolite expression
Protein sequences, families & motifs
Chemical biology
Reactions, interactions &
pathways
IntAct Reactome MetaboLights
Systems
BioModels Enzyme Portal BioSamples
Ensembl
Ensembl Genomes
GWAS Catalog
Metagenomics portal
Europe PubMed Central
Gene Ontology
Experimental Factor
Ontology
Literature & ontologies
5. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE Archive (in the context of ProteomeXchange
and the PSI standards)
• How to submit data to PRIDE: PRIDE tools
• How to access data in PRIDE Archive
• A sneak peak to other PRIDE resources
Overview
6. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE Archive (in the context of
ProteomeXchange and the PSI standards)
• How to submit data to PRIDE: PRIDE tools
• How to access data in PRIDE Archive
• A sneak peak to other PRIDE resources
Overview
7. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Mass Spectrometry (MS)-based proteomics
7
• Many different workflows.
• Discovery mode:
• Bottom-up proteomics
• Data dependent acquisition
• Data independent acquisition
• Top down proteomics
• Targeted mode:
• SRM (Selected Reaction
Monitoring)
8. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Mass Spectrometry (MS)-based proteomics
8
• Many different workflows.
• Discovery mode:
• Bottom-up proteomics
• Data dependent acquisition
• Data independent acquisition
• Top down proteomics
• Targeted mode:
• SRM (Selected Reaction
Monitoring)
9. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
MS proteomics: tandem MS (bottom-up)
MS/MS matching identifies
peptides, not proteins.
Proteins are inferred from the
peptide sequences.
10. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE stores mass spectrometry (MS)-
based proteomics data:
• Peptide and protein expression data
(identification and quantification)
• Post-translational modifications
• Mass spectra (raw data and peak
lists)
• Technical and biological metadata
• Any other related information
• Full support for tandem MS approaches
PRIDE (PRoteomics IDEntifications) database
http://www.ebi.ac.uk/pride/archive
Martens et al., Proteomics, 2005
Vizcaíno et al., NAR, 2013
11. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Mission
• To archive all types of proteomics mass
spectrometry data for the purpose of supporting
reproducible research, allowing the application of
quality control metrics and enabling the reuse of
these data by other researchers.
• To integrate MS-based data in a protein-centric
manner to provide information on protein variants,
modifications, and expression.
• To provide mass spectrometry based expression
data to the Expression Atlas.
12. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Mission
• To archive all types of proteomics mass
spectrometry data for the purpose of supporting
reproducible research, allowing the application of
quality control metrics and enabling the reuse of
these data by other researchers.
• To integrate MS-based data in a protein-centric
manner to provide information on protein variants,
modifications, and expression.
• To provide mass spectrometry based expression
data to the Expression Atlas.
13. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
What is a proteomics publication in 2015?
• Proteomics studies generate potentially large amounts of
data and results.
• Ideally, a proteomics publication needs to:
• Summarize the results of the study
• Provide supporting information for reliability of any
results reported
• Information in a publication:
• Manuscript
• Supplementary material
• Associated data submitted to a public repository
14. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Journal Submission Recommendations
• Journal guidelines recommend submission to proteomics
repositories:
Proteomics
Nature Biotechnology
Nature Methods
Molecular and Cellular Proteomics
• Funding agencies are enforcing public deposition of data
to maximize the value of the funds provided.
15. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE: Source of MS proteomics data
• PRIDE Archive already provides or
will soon provide MS proteomics
data to other EMBL-EBI resources
such as UniProt, Ensembl and the
EBI Expression Atlas.
http://www.ebi.ac.uk/pride/archive
16. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Data content in PRIDE Archive
• Dataset submission driven resource.
• PRIDE is organised in datasets (group of assays).
• An assay represents one MS run (in most cases).
• No data reprocessing at present. PRIDE aims to represent
the author’s view on the data.
• Main supported formats: PRIDE XML and mzIdentML.
• Raw data is also now stored.
17. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
ProteomeXchange Consortium
• Goal: Development of a framework to allow
standard data submission and dissemination
pipelines between the main existing proteomics
repositories.
• Includes PeptideAtlas (ISB, Seattle), PRIDE
(Cambridge, UK) and (very recently) MassIVE
(UCSD, San Diego).
• Common identifier space (PXD identifiers)
• Two supported data workflows: MS/MS and SRM.
• Main objective: Make life easier for researchers
http://www.proteomexchange.org
18. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
ProteomeCentral
Metadata /
Manuscript
Raw Data*
Results
Journals
UniProt/
neXtProt
Peptide Atlas
Other DBs
Receiving repositories
PASSEL
(SRM data)
PRIDE
(MS/MS data)
Other DBs
GPMDB
Researcher’s results
Reprocessed results
Raw data*
Metadata
MassIVE
(MS/MS data)
Vizcaíno et al., Nat Biotechnol, 2014
ProteomeXchange data workflow
19. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE Archive (in the context of ProteomeXchange
and the PSI standards)
• How to submit data to PRIDE: PRIDE tools
• How to access data in PRIDE Archive
• A sneak peak to other PRIDE resources
Overview
20. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
ProteomeCentral
Metadata /
Manuscript
Raw Data*
Results
Journals
UniProt/
neXtProt
Peptide Atlas
Other DBs
Receiving repositories
PASSEL
(SRM data)
PRIDE
(MS/MS data)
Other DBs
GPMDB
Researcher’s results
Reprocessed results
Raw data*
Metadata
MassIVE
(MS/MS data)
Vizcaíno et al., Nat Biotechnol, 2014
ProteomeXchange data workflow
21. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PX Data workflow for MS/MS data
1. Mass spectrometer output files: raw data (binary files) or
peak list spectra in a standardized format (mzML, mzXML).
2. Result files:
a. Complete submissions: Result files can be converted to
PRIDE XML or the mzIdentML data standard.
b. Partial submissions: For workflows not yet supported by
PRIDE, search engine output files will be stored and
provided in their original form.
3. Metadata: Sufficiently detailed description of sample origin,
workflow, instrumentation, submitter.
4. Other files: Optional files:
a. QUANT: Quantification related results e. FASTA
b. PEAK: Peak list files f. SP_LIBRARY
c. GEL: Gel images
d. OTHER: Any other file type
Published
Raw
Files
Other
files
22. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Complete
Partial
Complete vs Partial submissions: processed results
For complete submissions, it is possible to connect the spectra with the identification
processed results and they can be visualized.
23. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PX Data workflow for MS/MS data
1. Mass spectrometer output files: raw data (binary files) or
peak list spectra in a standardized format (mzML, mzXML).
2. Result files:
a. Complete submissions: Result files can be converted to
PRIDE XML or the mzIdentML data standard.
b. Partial submissions: For workflows not yet supported by
PRIDE, search engine output files will be stored and
provided in their original form.
3. Metadata: Sufficiently detailed description of sample origin,
workflow, instrumentation, submitter.
4. Other files: Optional files (the list can be extended):
a. QUANT: Quantification related results e. FASTA
b. PEAK: Peak list files f. SP_LIBRARY
c. GEL: Gel images
d. OTHER: Any other file type
Published
Raw
Files
Other
files
24. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Components: Submission Process
PRIDE Converter 2
PRIDE Inspector PX Submission Tool
mzIdentML
PRIDE XML
1
25. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Search
output
files
Spectra
files
Original data files ‘RESULT’ file generation Final ‘RESULT’ file
PRIDE
XML
‘RESULT’
Before: only file conversion to PRIDE XML
File conversion
PRIDE
Converter
Other tools, e.g. hEIDI
26. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PX Data workflow for MS/MS data
Search
Engine
Results +
MS files
PRIDE
Converter 2
PRIDE
XML
Coté & Griss et al., MCP, 2012
Other tools available:
- PRIDE Converter
- PLGS (Waters)
- Proteios
- EasyProt
- hEIDI
- OmicsHub (Integromics)
- PeptideShaker (Compomics)
PRIDE Converter 2
https://github.com/PRIDE-Toolsuite/pride-converter-2
- ‘Bulk’ conversion possible: Command Line mode
- Virtually no limit in file sizes.
27. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Tools ‘RESULT’ file generation Final ‘RESULT’ file
mzIdentML
‘RESULT’
Now: native file export to mzIdentML
Spectra
files
(mzML,
mzXML,
mzData,
mgf,
pkl,
ms2,
dta, apl)
Mascot
ProteinPilo
t
Scaffold
PEAKS
MSGF+
Others
Native File export
28. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Complete submissions
Search
Engine
Results +
MS files
Search
engines
mzIdentML
- Mascot
- MSGF+
- MyriMatch and related tools from D. Tabb’s lab
- OpenMS
- PEAKS
- PeptideShaker
- ProCon (ProteomeDiscoverer, Sequest)
- Scaffold
- TPP via the idConvert tool (ProteoWizard)
- ProteinPilot (from version 5.0)
- X!Tandem native conversion (Beta,
PILEDRIVER)
- Others: library for X!Tandem conversion, lab
internal pipelines, …
- Crux
An increasing number of tools support export to mzIdentML
1.1
- Referenced spectral files need to be submitted as well
(all open formats are supported).
Updated list: http://www.psidev.info/tools-implementing-
mzIdentML#.
29. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Components: Submission Process
PRIDE Converter 2
PRIDE Inspector PX Submission Tool
mzIdentML
PRIDE XML
2
30. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Inspector Toolsuite
Wang et al., Nat. Biotechnology, 2012
Perez-Riverol et al., MCP, 2016, in press
PRIDE Inspector
PRIDE Inspector Toolsuite supports:
- PRIDE XML
- mzIdentML + all types of spectra files
- mzML
- mzTab identification and Quantification +
all types of spectra files
https://github.com/PRIDE-Toolsuite/
31. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Inspector Toolsuite
https://github.com/PRIDE-Toolsuite/
New visualisation
functionality for Protein
Groups
PRIDE Inspector Toolsuite
32. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Inspector Toolsuite
PRIDE Inspector Toolsuite
Private review of files
submitted to PRIDE
https://github.com/PRIDE-Toolsuite/
33. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Components: Submission Process
PRIDE Converter 2
PRIDE Inspector PX Submission Tool
mzIdentML
PRIDE XML
3
34. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• Capture the mappings between the different types of files.
• Make the file upload process straightforward to the submitter (It transfers all the
files using Aspera or FTP).
PX submission tool
Published
Raw
Other
files
http://www.proteomexchange.org/submission
PX
submission
tool
• Command line alternative: Using the Aspera file transfer protocol.
37. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Manuscript published detailing the process
Ternent et al., Proteomics, 2014http://www.proteomexchange.org/submission
Example dataset:
PXD000764
- Title: “Discovery of new CSF biomarkers for meningitis in children”
- 12 runs: 4 controls and 8 infected samples
- Identification and quantification data
38. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Archive submitted datasets up until 1st November, 2015
• 1,259 submitted datasets by November 1st
• 923 submitted datasets in 2014
• In the last 6 months, 155 submitted datasets per month
• Size: ~ 160 TB.
39. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE: Size comparison with other EBI resources (May 2015)
1.E+07
1.E+08
1.E+09
1.E+10
1.E+11
1.E+12
1.E+13
1.E+14
1.E+15
1.E+16
1.E+17
2004 2006 2008 2010 2012 2014 2016
bytes
date
Data accumulation by resource
Metabolites
PRIDE
EGA
ENA (less AE)
AE
Chart generated by Guy Cochrane
40. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE Archive (in the context of ProteomeXchange
and the PSI standards)
• How to submit data to PRIDE: PRIDE tools
• How to access data in PRIDE Archive
• A sneak peak to other PRIDE resources
Overview
41. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Data access to PRIDE Archive
• Look for particular datasets of interest:
• For data reuse: which particular proteins and peptides
(including PTMs) have been detected.
• Data reinterpretation or re-analysis.
• Validation of the experimental results reported.
• Specific use cases for proteomics: spectral libraries,
fragmentation models, SRM transitions,…
42. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
RSS feed for public datasets
http://groups.google.com/group/proteomexchange/feed/rss_v2_0_msgs.xml
43. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Ways to access data in PRIDE Archive
• PRIDE web interface
• File repository
• REST web service
• PRIDE Inspector tool
46. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
ProteomeCentral
Metadata /
Manuscript
Raw Data*
Results
Journals
UniProt/
neXtProt
Peptide Atlas
Other DBs
Receiving repositories
PASSEL
(SRM data)
PRIDE
(MS/MS data)
Other DBs
GPMDB
Researcher’s results
Reprocessed results
Raw data*
Metadata
MassIVE
(MS/MS data)
Vizcaíno et al., Nat Biotechnol, 2014
ProteomeXchange data workflow
47. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
ProteomeCentral: Portal for all PX datasets
http://proteomecentral.proteomexchange.org/cgi/GetDataset
48. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• PRIDE Archive (in the context of ProteomeXchange
and the PSI standards)
• How to submit data to PRIDE: PRIDE tools
• How to access data in PRIDE Archive
• A sneak peak to other PRIDE resources
Overview
50. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
PRIDE Proteomes and PRIDE Cluster
• Provide an aggregated and QC filtered peptide-centric
and protein centric view on PRIDE Archive data.
http://www.ebi.ac.uk/pride/cluster/http://wwwdev.ebi.ac.uk/pride/proteomes/
51. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
• Main characteristics of PRIDE Archive and
ProteomeXchange (PX)
• PX/PRIDE submission workflow for MS/MS data
• PRIDE Inspector
• PX submission tool
• PRIDE/ProteomeXchange has become the de facto
standard for data submission and data availability in
proteomics
Conclusions
53. Juan A. Vizcaíno
juan@ebi.ac.uk
Training webinar
25 November 2015
Aknowledgements: People
Attila Csordas
Tobias Ternent
Noemi del Toro
Gerhard Mayer (Bochum, de.NBI)
Johannes Griss
Yasset Perez-Riverol
Henning Hermjakob
Former team members: Rui Wang,
Florian Reisinger and Jose A.
Dianes
Acknowledgements: The PRIDE Team
54. • 9 December – UniProt website updates
• 16 December – Ensembl release 83
All webinars @ 4:00pm GMT time unless stated
For details see: http://www.ebi.ac.uk/training/webinars
Future webinars: