Professor Carole Goble, University of Manchester, talks at the RIN "Research data: policies & behaviour" event as part of a series on Research Information in Transition.
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery.
The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
Marco Brandizi and Keywan Hassani-Pak, Rothamsted Research, Invited Presentation at SWAT4HCLS 2022.
FAIR data principles are being a driving force in life sciences and other scientific domains, helping researchers to share their data and free all of their potential to integrate information and do novel discoveries. Knowledge graphs are an ever more popular paradigm to model data according to such principles, and technologies such as graph databases are emerging as complementary to approaches like linked data. All of this includes the agronomy, farming and food domains. How advanced the adoption of sound data management policies is in these life domains? How does that compare to other life sciences? In this presentation, we will talk about our practical experience, focusing on KnetMiner, a gene and molecular biology discovering platform, which is based on building and publishing knowledge graphs according to the FAIR principles, as well as using a mix of linked data standards for life sciences and recent graph database and API technologies. We will welcome questions and discussions from the audience about similar experience.
Using KnetMiner to search and visualise the knowledge network of genes involved in neurodegenerative diseases such as Alzheimer, Parkinson and Huntington.
The Seven Deadly Sins of BioinformaticsDuncan Hull
Keynote talk at Bioinformatics Open Source Conference (BOSC) Special Interest Group at the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2007) in Vienna, July 2007 by Carole Goble, University of Manchester.
Model organisms such as budding yeast provide a common platform to interrogate and understand cellular and physiological processes. Knowledge about model organisms, whether generated during the course of scientific investigation, or extracted from published articles, are made available by model organism databases (MODs) such as the Saccharomyces Genome Database (SGD) for powerful, data-driven bioinformatic analyses. Integrative platforms such as InterMine offer a standard platform for MOD data exploration and data mining. Yet, today’s bioinformatic analyses also requires access to a significantly broader set of structured biomedical data, such as what can be found in the emerging network of Linked Open Data (LOD). If MOD data could be provisioned as FAIR (Findable, Accessible, Interoperable, and Reusable), then scientists could leverage a greater amount of interoperable data in knowledge discovery.
The goal of this proposal is to increase the utility of MOD data by implementing standards-compliant data access interfaces that interoperate with Linked Data. We will focus our efforts on developing interfaces for data access, data retrieval, and query answering for SGD. Our software will publish InterMine data as LOD that are semantically annotated with ontologies and be retrieved using standardized formats (e.g. JSON-LD, Turtle). We will facilitate the exploration of MOD data for hypothesis testing, by implementing efficient query answering using Linked Data Fragments, and by developing a set of graphical user interfaces to search for data of interest, explore connections, and answer questions that leverage the wider LOD network. Finally, we will develop a locally and cloud-deployable image to enable the rapid deployment of the proposed infrastructure. Our efforts to increase interoperability and ease of deployment for biomedical data repositories will increase research productivity and reduce costs associated with data integration and warehouse maintenance.
Marco Brandizi and Keywan Hassani-Pak, Rothamsted Research, Invited Presentation at SWAT4HCLS 2022.
FAIR data principles are being a driving force in life sciences and other scientific domains, helping researchers to share their data and free all of their potential to integrate information and do novel discoveries. Knowledge graphs are an ever more popular paradigm to model data according to such principles, and technologies such as graph databases are emerging as complementary to approaches like linked data. All of this includes the agronomy, farming and food domains. How advanced the adoption of sound data management policies is in these life domains? How does that compare to other life sciences? In this presentation, we will talk about our practical experience, focusing on KnetMiner, a gene and molecular biology discovering platform, which is based on building and publishing knowledge graphs according to the FAIR principles, as well as using a mix of linked data standards for life sciences and recent graph database and API technologies. We will welcome questions and discussions from the audience about similar experience.
Using KnetMiner to search and visualise the knowledge network of genes involved in neurodegenerative diseases such as Alzheimer, Parkinson and Huntington.
The Seven Deadly Sins of BioinformaticsDuncan Hull
Keynote talk at Bioinformatics Open Source Conference (BOSC) Special Interest Group at the 15th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2007) in Vienna, July 2007 by Carole Goble, University of Manchester.
With its focus on investigating the basis for the sustained existence
of living systems, modern biology has always been a fertile, if not
challenging, domain for formal knowledge representation and automated
reasoning. With thousands of databases and hundreds of ontologies now
available, there is a salient opportunity to integrate these for
discovery. In this talk, I will discuss our efforts to build a rich
foundational network of ontology-annotated linked data, develop
methods to intelligently retrieve content of interest, uncover
significant biological associations, and pursue new avenues for drug
discovery. As the portfolio of Semantic Web technologies continue to
mature in terms of functionality, scalability, and an understanding of
how to maximize their value, researchers will be strategically poised
to pursue increasingly sophisticated KR projects aimed at improving
our overall understanding of human health and disease.
bio: Dr. Michel Dumontier is an Associate Professor of Medicine
(Biomedical Informatics) at Stanford University. His research aims to
find new treatments for rare and complex diseases. His research
interest lie in the publication, integration, and discovery of
scientific knowledge. Dr. Dumontier serves as a co-chair for the World
Wide Web Consortium Semantic Web in Health Care and Life Sciences
Interest Group (W3C HCLSIG) and is the Scientific Director for
Bio2RDF, a widely used open-source project to create and provide
linked data for life sciences.
Making it Easier, Possibly Even Pleasant, to Author Rich Experimental MetadataMichel Dumontier
Biomedical researchers will remain stymied in their ability to take full advantage of the Big Data revolution if they can never find the datasets that they need to analyze, if there is lack of clarity about what particular datasets contain, and if data are insufficiently described.
CEDAR, an NIH BD2K Center of Excellence, aims to develop methods and tools to vastly ease the burden of authoring good experimental metadata, and to maximally use this information to zero in on datasets of interest.
A keynote given on experiences in curating workflows and web services.
3rd International Digital Curation Conference: "Curating our Digital Scientific Heritage: a Global Collaborative Challenge"
11-13 December 2007
Renaissance Hotel
Washington DC, USA
KnetMiner provides an easy to use web interface to visualisation and data mining tools for the discovery and evaluation of candidate genes from large scale integrations of public and private data sets. It addresses the needs of scientists who generally lack the time and technical expertise to review all relevant information available in the literature, from key model species and from a potentially wide range of related biological databases. We have previously developed genome-scale knowledge networks (GSKNs) for multiple crop and animal species (Hassani-Pak et al. 2016). The KnetMiner web server searches and evaluates millions of relations and concepts within the GSKNs in real-time to determine if direct or indirect links between genes and trait-based keywords can be established. KnetMiner accepts as user inputs: search terms in combination with a gene list and/or genomic regions. It produces a table of ranked candidate genes and allows users to explore the output in interactive genome and network map visualisation tools that have been optimised for web use on desktop and mobile devices. The KnetMiner web server and the GSKNs provide a step-forward towards systematic and evidence-based gene discovery.
In the late Fall and Winter of 2018, the Pistoia Alliance in cooperation with Elsevier and charitable organizations Cures within Reach and Mission: Cure ran a datathon aiming to find drugs suitable for treatment of childhood chronic pancreatitis, a rare disease that causes extreme suffering. The datathon resulted in identification of four candidate compounds in a short time frame of just under three months. In this webinar our speakers discuss the technologies that made this leap possible
Introducing the KnetMiner Knowledge Graph: things, not stringsKeywan Hassani-Pak
Rothamsted Seminar Series by Keywan Hassani-Pak, 1 April 2019
Researchers at Rothamsted and around the world are working to push the boundaries of human knowledge. One would think they have access to the best available tools to help them in their quest for knowledge. In reality the opposite is often true: the research tools at our disposal are only substandard and therefore searching and discovering new biological clues still requires a lot of hard work. We have developed an intelligent data model, known as the KnetMiner Knowledge Graph, that helps researchers to discover new information quickly and easily. Knowledge graphs are commonly used to represent biological entities and their relationships to one another: i.e. things, not strings. Our wheat Knowledge Graph, for example, currently contains more than 1.5 million objects and 6 million facts about, and relations between, these different objects. KnetMiner (www.knetminer.org) enables you to search the Knowledge Graph for genes, phenotypes, diseases, stresses, molecules and more - and instantly tell you the stories of complex traits.
Slides for the afternoon session on "Introduction to Bioinformatics", delivered at the James Hutton Institute, 29th, 20th May and 5th June 2014, by Leighton Pritchard and Peter Cock.
Slides cover introductory guidance and links to resources, theory and use of BLAST tools, and a workshop featuring some common tools and tasks.
In recent years there has been a dramatic increase in the number of freely accessible online databases serving the chemistry community. The internet provides chemistry data that can be used for data-mining, for computer models, and integration into systems to aid drug discovery. There is however a responsibility to ensure that the data are high quality to ensure that time is not wasted in erroneous searches, that models are underpinned by accurate data and that improved discoverability of online resources is not marred by incorrect data. In this article we provide an overview of some of the experiences of the authors using online chemical compound databases, critique the approaches taken to assemble data and we suggest approaches to deliver definitive reference data sources.
Excited to share our vision for bioinformatics education available for students and researchers that want to apply advanced multi-omics integration and machine learning to large biomedical datasets. Practice and learn from real-life projects.
With the explosion of interest in both enhanced knowledge management and open science, the past few years have seen considerable discussion about making scientific data “FAIR” — findable, accessible, interoperable, and reusable. The problem is that most scientific datasets are not FAIR. When left to their own devices, scientists do an absolutely terrible job creating the metadata that describe the experimental datasets that make their way in online repositories. The lack of standardization makes it extremely difficult for other investigators to locate relevant datasets, to re-analyse them, and to integrate those datasets with other data. The Center for Expanded Data Annotation and Retrieval (CEDAR) has the goal of enhancing the authoring of experimental metadata to make online datasets more useful to the scientific community. The CEDAR work bench for metadata management will be presented in this webinar. CEDAR illustrates the importance of semantic technology to driving open science. It also demonstrates a means for simplifying access to scientific data sets and enhancing the reuse of the data to drive new discoveries.
Can machines understand the scientific literaturepetermurrayrust
With over 5000 scientific articles per day we need machines to help us understand the content. This material is to be used at an interactive session for the Science Society at Trinity College Cambridge UK
Bioinformatics, Its Usage and Advantagesbioinformatt
Bioinformatics is one of the major and important fields of biological sciences. Although it is a new discipline; however, it is developing at much faster rate. There are so many experts that are associated with this field.
Packed with speaking points and useful facts that support your case, this template will help build a confident and well-developed business case on how web content management can:
- Decrease operational web costs while increasing the bottom line
- Solve business challenges
- Expands web footprint
- Enable Fresh, Consistent, and High Quality Content
Percussion has made web content management a true software product with the ability to import your current site so you can be live in days. Request a 45 minute Demo today: http://bit.ly/ZaBVmd
With its focus on investigating the basis for the sustained existence
of living systems, modern biology has always been a fertile, if not
challenging, domain for formal knowledge representation and automated
reasoning. With thousands of databases and hundreds of ontologies now
available, there is a salient opportunity to integrate these for
discovery. In this talk, I will discuss our efforts to build a rich
foundational network of ontology-annotated linked data, develop
methods to intelligently retrieve content of interest, uncover
significant biological associations, and pursue new avenues for drug
discovery. As the portfolio of Semantic Web technologies continue to
mature in terms of functionality, scalability, and an understanding of
how to maximize their value, researchers will be strategically poised
to pursue increasingly sophisticated KR projects aimed at improving
our overall understanding of human health and disease.
bio: Dr. Michel Dumontier is an Associate Professor of Medicine
(Biomedical Informatics) at Stanford University. His research aims to
find new treatments for rare and complex diseases. His research
interest lie in the publication, integration, and discovery of
scientific knowledge. Dr. Dumontier serves as a co-chair for the World
Wide Web Consortium Semantic Web in Health Care and Life Sciences
Interest Group (W3C HCLSIG) and is the Scientific Director for
Bio2RDF, a widely used open-source project to create and provide
linked data for life sciences.
Making it Easier, Possibly Even Pleasant, to Author Rich Experimental MetadataMichel Dumontier
Biomedical researchers will remain stymied in their ability to take full advantage of the Big Data revolution if they can never find the datasets that they need to analyze, if there is lack of clarity about what particular datasets contain, and if data are insufficiently described.
CEDAR, an NIH BD2K Center of Excellence, aims to develop methods and tools to vastly ease the burden of authoring good experimental metadata, and to maximally use this information to zero in on datasets of interest.
A keynote given on experiences in curating workflows and web services.
3rd International Digital Curation Conference: "Curating our Digital Scientific Heritage: a Global Collaborative Challenge"
11-13 December 2007
Renaissance Hotel
Washington DC, USA
KnetMiner provides an easy to use web interface to visualisation and data mining tools for the discovery and evaluation of candidate genes from large scale integrations of public and private data sets. It addresses the needs of scientists who generally lack the time and technical expertise to review all relevant information available in the literature, from key model species and from a potentially wide range of related biological databases. We have previously developed genome-scale knowledge networks (GSKNs) for multiple crop and animal species (Hassani-Pak et al. 2016). The KnetMiner web server searches and evaluates millions of relations and concepts within the GSKNs in real-time to determine if direct or indirect links between genes and trait-based keywords can be established. KnetMiner accepts as user inputs: search terms in combination with a gene list and/or genomic regions. It produces a table of ranked candidate genes and allows users to explore the output in interactive genome and network map visualisation tools that have been optimised for web use on desktop and mobile devices. The KnetMiner web server and the GSKNs provide a step-forward towards systematic and evidence-based gene discovery.
In the late Fall and Winter of 2018, the Pistoia Alliance in cooperation with Elsevier and charitable organizations Cures within Reach and Mission: Cure ran a datathon aiming to find drugs suitable for treatment of childhood chronic pancreatitis, a rare disease that causes extreme suffering. The datathon resulted in identification of four candidate compounds in a short time frame of just under three months. In this webinar our speakers discuss the technologies that made this leap possible
Introducing the KnetMiner Knowledge Graph: things, not stringsKeywan Hassani-Pak
Rothamsted Seminar Series by Keywan Hassani-Pak, 1 April 2019
Researchers at Rothamsted and around the world are working to push the boundaries of human knowledge. One would think they have access to the best available tools to help them in their quest for knowledge. In reality the opposite is often true: the research tools at our disposal are only substandard and therefore searching and discovering new biological clues still requires a lot of hard work. We have developed an intelligent data model, known as the KnetMiner Knowledge Graph, that helps researchers to discover new information quickly and easily. Knowledge graphs are commonly used to represent biological entities and their relationships to one another: i.e. things, not strings. Our wheat Knowledge Graph, for example, currently contains more than 1.5 million objects and 6 million facts about, and relations between, these different objects. KnetMiner (www.knetminer.org) enables you to search the Knowledge Graph for genes, phenotypes, diseases, stresses, molecules and more - and instantly tell you the stories of complex traits.
Slides for the afternoon session on "Introduction to Bioinformatics", delivered at the James Hutton Institute, 29th, 20th May and 5th June 2014, by Leighton Pritchard and Peter Cock.
Slides cover introductory guidance and links to resources, theory and use of BLAST tools, and a workshop featuring some common tools and tasks.
In recent years there has been a dramatic increase in the number of freely accessible online databases serving the chemistry community. The internet provides chemistry data that can be used for data-mining, for computer models, and integration into systems to aid drug discovery. There is however a responsibility to ensure that the data are high quality to ensure that time is not wasted in erroneous searches, that models are underpinned by accurate data and that improved discoverability of online resources is not marred by incorrect data. In this article we provide an overview of some of the experiences of the authors using online chemical compound databases, critique the approaches taken to assemble data and we suggest approaches to deliver definitive reference data sources.
Excited to share our vision for bioinformatics education available for students and researchers that want to apply advanced multi-omics integration and machine learning to large biomedical datasets. Practice and learn from real-life projects.
With the explosion of interest in both enhanced knowledge management and open science, the past few years have seen considerable discussion about making scientific data “FAIR” — findable, accessible, interoperable, and reusable. The problem is that most scientific datasets are not FAIR. When left to their own devices, scientists do an absolutely terrible job creating the metadata that describe the experimental datasets that make their way in online repositories. The lack of standardization makes it extremely difficult for other investigators to locate relevant datasets, to re-analyse them, and to integrate those datasets with other data. The Center for Expanded Data Annotation and Retrieval (CEDAR) has the goal of enhancing the authoring of experimental metadata to make online datasets more useful to the scientific community. The CEDAR work bench for metadata management will be presented in this webinar. CEDAR illustrates the importance of semantic technology to driving open science. It also demonstrates a means for simplifying access to scientific data sets and enhancing the reuse of the data to drive new discoveries.
Can machines understand the scientific literaturepetermurrayrust
With over 5000 scientific articles per day we need machines to help us understand the content. This material is to be used at an interactive session for the Science Society at Trinity College Cambridge UK
Bioinformatics, Its Usage and Advantagesbioinformatt
Bioinformatics is one of the major and important fields of biological sciences. Although it is a new discipline; however, it is developing at much faster rate. There are so many experts that are associated with this field.
Packed with speaking points and useful facts that support your case, this template will help build a confident and well-developed business case on how web content management can:
- Decrease operational web costs while increasing the bottom line
- Solve business challenges
- Expands web footprint
- Enable Fresh, Consistent, and High Quality Content
Percussion has made web content management a true software product with the ability to import your current site so you can be live in days. Request a 45 minute Demo today: http://bit.ly/ZaBVmd
Book Rapper 'We Blog' is a RAP of Michael A Banks "Blogging Heroes". In this slideshow we introduce you to the major ideas including: Why Blog? The Blogging Medium, Making Money from your blog and more...
Presentation from RIN hosted event on 'The future of scholarly publishing - where do we go from here?'
Part one of a series of events on the theme 'Research information in transition'.
Being FAIR: FAIR data and model management SSBSS 2017 Summer SchoolCarole Goble
Lecture 1:
Being FAIR: FAIR data and model management
In recent years we have seen a change in expectations for the management of all the outcomes of research – that is the “assets” of data, models, codes, SOPs, workflows. The “FAIR” (Findable, Accessible, Interoperable, Reusable) Guiding Principles for scientific data management and stewardship [1] have proved to be an effective rallying-cry. Funding agencies expect data (and increasingly software) management retention and access plans. Journals are raising their expectations of the availability of data and codes for pre- and post- publication. The multi-component, multi-disciplinary nature of Systems and Synthetic Biology demands the interlinking and exchange of assets and the systematic recording of metadata for their interpretation.
Our FAIRDOM project (http://www.fair-dom.org) supports Systems Biology research projects with their research data, methods and model management, with an emphasis on standards smuggled in by stealth and sensitivity to asset sharing and credit anxiety. The FAIRDOM Platform has been installed by over 30 labs or projects. Our public, centrally hosted Asset Commons, the FAIRDOMHub.org, supports the outcomes of 50+ projects.
Now established as a grassroots association, FAIRDOM has over 8 years of experience of practical asset sharing and data infrastructure at the researcher coal-face ranging across European programmes (SysMO and ERASysAPP ERANets), national initiatives (Germany's de.NBI and Systems Medicine of the Liver; Norway's Digital Life) and European Research Infrastructures (ISBE) as well as in PI's labs and Centres such as the SynBioChem Centre at Manchester.
In this talk I will show explore how FAIRDOM has been designed to support Systems Biology projects and show examples of its configuration and use. I will also explore the technical and social challenges we face.
I will also refer to European efforts to support public archives for the life sciences. ELIXIR (http:// http://www.elixir-europe.org/) the European Research Infrastructure of 21 national nodes and a hub funded by national agreements to coordinate and sustain key data repositories and archives for the Life Science community, improve access to them and related tools, support training and create a platform for dataset interoperability. As the Head of the ELIXIR-UK Node and co-lead of the ELIXIR Interoperability Platform I will show how this work relates to your projects.
[1] Wilkinson et al, The FAIR Guiding Principles for scientific data management and stewardship Scientific Data 3, doi:10.1038/sdata.2016.18
FAIR Data, Operations and Model management for Systems Biology and Systems Me...Carole Goble
FAIR Data, Operations and Model management for Systems Biology and Systems Medicine Projects given at 1st Conference of the European Association of Systems Medicine, 26-28 October 2016, Berlin. the FAIRDOM project is described.
WikiPathways: how open source and open data can make omics technology more us...Chris Evelo
Presentation about collaborative development of open source pathway analysis code and pathways and about usage in analytical software distributed with analytical machines like mass spectrophotometers.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool.
DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Building bioinformatics resources for the global communityExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
Building bioinformatics resources for the global community. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management and GMI-9, 23-25 May 2016, Rome, Italy.
A Step to the Clouded Solution of Scalable Clinical Genome Sequencing (BDT308...Amazon Web Services
Professors Wall and Tonellato of Harvard Medical School in collaboration with Beth Israel Deaconess Medical Center discuss the emerging area of clinical whole genome sequencing analysis and tools. They report on the use of Amazon EC2 and Spot Instances to achieve a robust clinical time processing solution and examine the barriers to and resolution of producing clinical-grade whole genome results in the cloud. They benchmark an AWS solution, called COSMOS, against local computing solutions and demonstrate the time and capacity gains conferred through the use of AWS.
Workshop finding and accessing data - fiona nadia charlotte - cambridge apr...Fiona Nielsen
Workshop presentation on finding and accessing human genomics data for research.
Including statistics of publicly available data sources and tips on how to save time in your workflow of data access.
Organised in collaboration between DNAdigest and Open Data Cambridge.
Read more about our work:
http://DNAdigest.org
http://repositive.io
https://uk.linkedin.com/in/fionanielsen
http://www.data.cam.ac.uk
Results Vary: The Pragmatics of Reproducibility and Research Object FrameworksCarole Goble
Keynote presentation at the iConference 2015, Newport Beach, Los Angeles, 26 March 2015.
Results Vary: The Pragmatics of Reproducibility and Research Object Frameworks
http://ischools.org/the-iconference/
BEWARE: presentation includes hidden slides AND in situ build animations - best viewed by downloading.
A Big Picture in Research Data ManagementCarole Goble
A personal view of the big picture in Research Data Management, given at GFBio - de.NBI Summer School 2018 Riding the Data Life Cycle! Braunschweig Integrated Centre of Systems Biology (BRICS), 03 - 07 September 2018
Large scale machine learning challenges for systems biologyMaté Ongenaert
Large scale machine learning challenges for systems biology
by dr. Yvan Saeys - Machine Learning and Data Mining group, Bioinformatics and Systems Biology Division, VIB-UGent Department of Plant Systems Biology
Due to technological advances, the amount of biological data, and the pace at which it is generated has increased dramatically during the past decade. To extract new knowledge from these ever increasing data sets, automated techniques such as data mining and machine learning techniques have become standard practice.
In this talk, I will give an overview of large scale machine learning challenges in bioinformatics and systems biology, highlighting the importance of using scalable and robust techniques such as ensemble learning methods implemented on large computing grids.
I will present some of our state-of-the-art tools to solve problems such as biomarker discovery, large scale network inference, and biomedical text mining at PubMed scale.
Workshop finding and accessing data - fiona - lunteren april 18 2016Fiona Nielsen
Workshop presentation on finding and accessing human genomics data for research.
Including statistics of publicly available data sources and tips on how to save time in your workflow of data access.
Presented at BioSB2016, pre-conference PhD retreat for young researchers in bioinformatics and systems biology at Congrescentrum De Werelt in Lunteren. #BioSB2016 #BioSB16
Link to event:
http://www.youngcb.nl/events/biosb-phd-retreat-2016/
Read more about my work:
http://DNAdigest.org
http://repositive.io
https://uk.linkedin.com/in/fionanielsen
Presentation by Michael Jubb, Director of Research Information Network, given at the Preservation Advisory Centre 'Decoding the Digital' conference at the British Library 27 July 2010.
Presentation by RIN Director Michael Jubb at Dryad repository for datasets workshop linked to published journal articles (http://datadryad.org/repo)
on 27 April 2010, London
Presentation by the RIN's Director, Michael Jubb, at the Spanish Research Council's (CSIC) workshop on the politics of the promotion of open access in Barcelona in March 2010. http://www.csic.es/web/guest/home
Presentation by RIN's Director, Michael Jubb, at the Association of Subscription Agents' annual conference in February 2010. http://www.subscription-agents.org/conferences/asa-conference-2010
Presentation by the RIN's Liaison and Partnership Officer, Branwen Hide, at the British Library/JISC Digital Researchers Day on 15 March 2010 (http://explorationforchange.net/index.php/current-projects/researchers-of-tomorrow/researchers-of-tomorrow-home.html).
Covers different types of news readers/aggregators that might be of use to researchers and how to use them.
Sense About Science held a workshop on peer review in collaboration with the Research Information Network, Vitae, Elsevier and the Voice of Young Science.
This afternoon event was held at the University of Sussex, Brighton on 5 March 2010 and was free and for early career researchers in all sciences, engineering and medicine (PhD students, post-docs or equivalent in first job).
The workshop discussed the process of peer review in journal publishing and explored the criticisms of the peer review process. What does peer review do for science? Does it detect fraud and misconduct? Will it illuminate good ideas or shut them down?
The RIN’s Liason and Partnerships Officer, Branwen Hide, spoke at the event on ‘The changing scholarly communications landscape: What does this mean for peer review?’
For more information on the programme, visit http://www.rin.ac.uk/news/events/research-publishing-it-reviewing-it-and-talking-about-it-publicly
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Data sharing - Data management - The SysMO-SEEK Story
1. Data sharing
Data management
The SysMO-SEEK
Story
Professor Carole Goble FREng FBCS CITP
University of Manchester, UK
carole.goble@manchester.ac.uk
2. 13 teams
91 institutes, 300 scientists
Multi-site, multi-disciplinary
Each three year duration
Data generation
Data consumption
Data analysis
Data management:
Local – Shared – Long term
Pan European
Systems Biology
http://www.sysmo.net
3.
4. Own data solutions. wikis, e-Groupware,
PHProjekt, BaseCamp, PLONE, Alfresco, bespoke
commercial … files and spreadsheets.
Extreme caution over sharing.
Modellers vs experimentalist tribalism
Many institutions, many projects, overlapping
memberships, changing membership. Projects
ending, starting, carrying on the same, carrying
on differently.
Legacy
Suspicion
Dynamics
Expert scientists, inexpert informaticians. Few
resources.
Skills
Patchy standards, incomparable data,
afterthought.
Data
6. Data mine-ing
“my impression of researchers, and I can
criticize myself in this, is that we’re much
more interested in sharing data when we
mean sharing somebody else’s as opposed
[to] sharing ours.”
E-infrastructure - taking forward the strategy, RIN report, 2010
8. “It’s not ready yet”
“I need to get (another) publication first”
“We don’t have the resources or skills to prepare
it for others, esp. now we finished that project”
“Its faster/easier to do it myself, and will keep the
credit/control too”
“Its not described enough to be usable”
“I don’t trust the quality. Its not reliable enough. Its
too noisy.
“Others won’t use it properly.”
“It’s not worth
my while”“They are my competitors!!”
10. 2. Preparation for Use
Curation
Standards
Reusability
Reproducibility
Accountability & Quality
Data discipline Silo busting
11. CIMR Core Information for Metabolomics Reporting
MIABE Minimal Information About a Bioactive Entity
MIACA Minimal Information About a Cellular Assay
MIAME Minimum Information About a Microarray Experiment
MIAME/Env MIAME / Environmental transcriptomic experiment
MIAME/Nutr MIAME / Nutrigenomics
MIAME/Plant MIAME / Plant transcriptomics
MIAME/Tox MIAME / Toxicogenomics
MIAPA Minimum Information About a Phylogenetic Analysis
MIAPAR Minimum Information About a Protein Affinity Reagent
MIAPE Minimum Information About a Proteomics Experiment
MIARE Minimum Information About a RNAi Experiment
MIASE Minimum Information About a Simulation Experiment
MIENS Minimum Information about an ENvironmental Sequence
MIFlowCyt Minimum Information for a Flow Cytometry Experiment
MIGen Minimum Information about a Genotyping Experiment
MIGS Minimum Information about a Genome Sequence
MIMIx Minimum Information about a Molecular Interaction Experiment
MIMPP Minimal Information for Mouse Phenotyping Procedures
MINI Minimum Information about a Neuroscience Investigation
MINIMESS Minimal Metagenome Sequence Analysis Standard
MINSEQE Minimum Information about a high-throughput SeQuencing Experiment
MIPFE Minimal Information for Protein Functional Evaluation
MIQAS Minimal Information for QTLs and Association Studies
MIqPCR Minimum Information about a quantitative Polymerase Chain Reaction experiment
MIRIAM Minimal Information Required In the Annotation of biochemical Models
MISFISHIE Minimum Information Specification For In Situ Hybridization and Immunohistochemistry
Experiments
STRENDA Standards for Reporting Enzymology Data
TBC Tox Biology Checklist
BioPAX : Biological Pathways Exchange http://www.biopax.org/
FuGE Functional Genomics Experimenthttp://www.mibbi.org/index.php/MIBBI_portal
Minimum
Information for
Biological and
Biomedical
Investigations
Metadata Minefield
14. Blue Collar Science
John Quackenbush
Difficult
and time
consuming
Poor Credit
or Reward
Shabby
Career
Paths &
Prospects
15. 3. Credit Crisis
• Reward sharing, curation and
reuse rather than reinvention.
• Credit. Attribution. Citation.
• For software, methods and
standards too.
• Technical (DataCite.org).
• Cultural (Respected policy).
• Institutional.
• Funding bodies.
16. 4. Infrastructure, Capability & Capacity
• Three year
PhD/project cycle
• Local data control
• Realistic paths to
adoption by busy
people.
• Spreadsheets, wikis,
catalogues and
yellow pages.
• Content and Tools
18. 6. Sustained Resources
• Three year projects.
• Three year lifespan of data (and its software).
• Sunsets and Sustains
• Reinvention rewarded
• Institution.
• Funding councils.
• Funding panels.
• Publishers
• Libraries
• National data centres
• International data centres
20. A Partnership
• Software engineers
• Computational scientists
• Experimental Scientists
• Domain informaticians
• Service providers
• Funding agencies
• But the community
credit crisis continues….
21. Summary
• Science is a complex social activity
undertaken by tribes of people and
dominated by trust issues.
• Infrastructure has to be there and fit for
purpose but its not the real the problem.
• Need a cultural shift (on all sides) that
truly honours data.
Editor's Notes
Learn about JISC’s work in the area of shared services for STEM subjects, particularly the JANET network service and virtual research environments (i.e., web tools for helping research processes)
Explore new opportunities for research being opened up via shared services, and also the economic savings this creates
Consider the role their university might play in providing a shared service to other institutions
Nor major data centres but long tail
Data pipeline
Data funnel
Fuzzy line between collaborators and competitors
Usb drives, wikis, databadsaes,
Disributed in email etc.
Sharing without fear
MaDaM project
Competitive advantage.
Academic vanity.
Adoption.
Reputation.
Acceleration.
Novel insights.
Help.
Scrutiny.
Being scooped.
Misinterpretation.
Reputation.
Trust.
Not comprehensible
Competitive advantage.
Academic vanity.
Reputation.
Adoption
Scrutiny.
Being scooped.
Misinterpretation.
New Reward Schemes
But we have to aware of the drivers for collaboration.
Competitive advantage.
Be the first with the Nature paper.
Academic vanity
Credit, credibility, fame, acclaim,
recognition, peer respect, reputation.
Adoption
Get my stuff adopted / recognised
More funding
Being found out
Open to rigorous inspection.
Being scooped
Beaten by lab X
Protecting my turf.
Releasing results too early.
Getting left behind. Being out of fashion.
Looking stupid
Being misinterpreted or misrepresented.
Looking stupid. Losing control. Taking a risk
Some excuses
Genomics Standards Consortium
http://gensc.org/gc_wiki/index.php/MIBBI_workshop
All or nothing
Credit, Citation, Career
Personal and institutional visibility
Scholarly citation metrics
contribute, curate, review, reuse.
Data is not respected
. John Quackenbush - John Quackenbush - Professor of Computational Biology and Bioinformatics - Department of Biostatistics - Harvard School of Public Health.
58% developed by students, 24% stated not maintained
(Schultheiss et al. (2010) PLoS Comp Biol (in review))
Tools, commons
Preparing data for sharing is free like puppies are free
National Centre for BioOntologies
The Open Biological and Biomedical Ontologies
Standardise messages not structures
Only as good as your data services
Minimum models and Controlled vocabularies
63%
47%
58% developed by students, 24% stated not maintained
(Schultheiss et al. (2010) PLoS Comp Biol (in review))
Tools, commons
Preparing data for sharing is free like puppies are free
Doi’s cost
Hard core are the PALs
Commons-based Cleanup
● Manual and automated curation workflows ● Curators emergent and assigned ● Curation tools
Incentives
Right time right place – also email!
Third party curation is really hard
Expert curation
Classification
Weeding
Added value
Structured metadata
Prompting
Classification
Filtering
Facetted browsing
Time to get organised
One example workflow can be found at: http://www.myexperiment.org/workflows/16 This the the old example workflow, but I have tagged as a benchmark. You can see the breakdown of tags given to this at: http://www.myexperiment.org/workflows/16/curation ... or by clicking on the breakdown section (see attached image). 14 curation tags Some are slightly ambiguous and others have little meaning These were: * test workflow * component - part of whole solution * whole solution * tutorial / example * incomplete * junk * obsolete - deprecated * runnable * not runnable * requires description * requires credit / attribution * requires example input data * description; [Description Text] * example data; [port : value] Each tag was preceeded by a "c:" so that it would be picked up by the myExperiment plugin and could be differentiated from other myExperiment tags. If some example data was known, I tried to add it to using the example tag "example data; [port : value]", where the port name is given, along with the data to be put into the port. The whole process was very time consuming, as I had to try and open each workflow in T2, run it using some example data (or figure out what it did and run it with lots of test data), and then add each comment (checking each workflow on myExperiment to see if it had complete properly.
Add url here
E-Lab and Taverna – all my software - elephants ---- elephant in the room, blind men and elephants, danger of being white elephants?
SysMO
And other e-Science projects
Each of these apply to all our projects. Just one of them is not enough. Not even for Taverna.
To sustain it as a service we must sustain the software and the content in its repositories