Presentation on the EBI linked data, given at the SIB course on linked data for life science, Dec 2015.
This is a PDF version of the original presentation available on Prezi: http://tinyurl.com/ebirdfsib15
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.
Sharing data with lightweight data standards, such as schema.org and bioschemas. The Knetminer case, an application for the agrifood domain and molecular biology.
Presented at Open Data Sicilia (#ODS2021)
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.
Sharing data with lightweight data standards, such as schema.org and bioschemas. The Knetminer case, an application for the agrifood domain and molecular biology.
Presented at Open Data Sicilia (#ODS2021)
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
This workshop aims at gathering together practioners of all levels and from a variety of research areas (agronomy, plant biology, food, life sciences etc) to compare best practices, points of views and projects about producing and consuming data in the agrifood field.
As it happens in general for digital data, the current trends in this arena include integration of "traditional" semantic-based approaches (eg, ontoloies, RDF-based linked data) with lightweight schemas (eg, Bioschemas/schema.org), use of JSON-based APIs, development of data lakes and knowledge graphs based on NoSQL technologies, graph databases based on property graphs (eg, Neo4j, TinkerPop/Gremlin).
Workshop participants will get an opportunity to discuss how those approaches and technologies are being used in the agrifood field, for the purpose or realising the FAIR data principles and make data sharing a powerful tool for research, industry or socio-economic investigation. In particular, we will propose an interactive session to outline the way participant-proposed datasets can be encoded through bioschemas or similar approaches.
Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMine...Rothamsted Research, UK
Graph-based modelling is becoming more popular, in the sciences and elsewhere, as a flexible and powerful way to exploit data to power world-changing digital applications. Com- pared to the initial vision of the Semantic Web, knowledge graphs and graph databases are be- coming a practical and computationally less formal way to manage graph data. On the other hand, linked data based on Semantic Web standards are a complementary, rather than alternative, ap- proach to deal with these data, since they still provide a common way to represent and exchange information. In this paper we introduce rdf2neo, a tool to populate Neo4j databases starting from RDF data sets, based on a configurable mapping between the two. By employing agrigenomics- related real use cases, we show how such mapping can allow for a hybrid approach to the man- agement of networked knowledge, based on taking advantage of the best of both RDF and prop- erty graphs.
Some considerations on using the two systems to manage molecular biology knowledge networks. This comes from: https://github.com/marco-brandizi/odx_neo4j_converter_test
Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and...Rothamsted Research, UK
Presented at Integrative Bioinformatics Conference (IB2018, Harpenden, 2018).
We describe how to use Semantic Web Technologies and graph databases like Neo4j to serve life science data and address the FAIR data principles.
Behind the Scenes of KnetMiner: Towards Standardised and Interoperable Knowle...Rothamsted Research, UK
Workshop within the Integrative Bioinformatics Conference (IB2018, Harpenden, 2018).
We describe how to use Semantic Web Technologies and graph databases like Neo4j to serve life science data and address the FAIR data principles.
graph2tab, a library to convert experimental workflow graphs into tabular for...Rothamsted Research, UK
a generic implementation of a method for producing spreadsheets out of pipeline graphs See https://github.com/ISA-tools/graph2tab for details.
Presentation given to my group at EBI, on Feb 2, 2012.
Building Linked Data for the EBI RDF Platform and biomedical samples: what we have learned and delivered during the Biomedbridges project. Original @ https://prezi.com/vxox0pgra6d7/biosd-linked-data-lessons-learned/
myequivalents is a system to manage cross-references between entities that can be identified by pairs composed of a service name (e.g., EBI's ArrayExpress, Wikipedia) and an accession (e.g., E-MEXP-2514, Barack_Obama). For those familiar with the Semantic Web, we plan to support identification of entities via URIs and the owl:sameAs property. For those who already know MIRIAM and identifiers.org, myequivalents is more general than them and we plan to support these services in future.
A few notes here about the UK Ontology Network Meeting (http://dream.inf.ed.ac.uk/events/ukont-13/2013_workshop_program.html) I've attended on 11/Apr/2013.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
This workshop aims at gathering together practioners of all levels and from a variety of research areas (agronomy, plant biology, food, life sciences etc) to compare best practices, points of views and projects about producing and consuming data in the agrifood field.
As it happens in general for digital data, the current trends in this arena include integration of "traditional" semantic-based approaches (eg, ontoloies, RDF-based linked data) with lightweight schemas (eg, Bioschemas/schema.org), use of JSON-based APIs, development of data lakes and knowledge graphs based on NoSQL technologies, graph databases based on property graphs (eg, Neo4j, TinkerPop/Gremlin).
Workshop participants will get an opportunity to discuss how those approaches and technologies are being used in the agrifood field, for the purpose or realising the FAIR data principles and make data sharing a powerful tool for research, industry or socio-economic investigation. In particular, we will propose an interactive session to outline the way participant-proposed datasets can be encoded through bioschemas or similar approaches.
Getting the best of Linked Data and Property Graphs: rdf2neo and the KnetMine...Rothamsted Research, UK
Graph-based modelling is becoming more popular, in the sciences and elsewhere, as a flexible and powerful way to exploit data to power world-changing digital applications. Com- pared to the initial vision of the Semantic Web, knowledge graphs and graph databases are be- coming a practical and computationally less formal way to manage graph data. On the other hand, linked data based on Semantic Web standards are a complementary, rather than alternative, ap- proach to deal with these data, since they still provide a common way to represent and exchange information. In this paper we introduce rdf2neo, a tool to populate Neo4j databases starting from RDF data sets, based on a configurable mapping between the two. By employing agrigenomics- related real use cases, we show how such mapping can allow for a hybrid approach to the man- agement of networked knowledge, based on taking advantage of the best of both RDF and prop- erty graphs.
Some considerations on using the two systems to manage molecular biology knowledge networks. This comes from: https://github.com/marco-brandizi/odx_neo4j_converter_test
Towards FAIRer Biological Knowledge Networks Using a Hybrid Linked Data and...Rothamsted Research, UK
Presented at Integrative Bioinformatics Conference (IB2018, Harpenden, 2018).
We describe how to use Semantic Web Technologies and graph databases like Neo4j to serve life science data and address the FAIR data principles.
Behind the Scenes of KnetMiner: Towards Standardised and Interoperable Knowle...Rothamsted Research, UK
Workshop within the Integrative Bioinformatics Conference (IB2018, Harpenden, 2018).
We describe how to use Semantic Web Technologies and graph databases like Neo4j to serve life science data and address the FAIR data principles.
graph2tab, a library to convert experimental workflow graphs into tabular for...Rothamsted Research, UK
a generic implementation of a method for producing spreadsheets out of pipeline graphs See https://github.com/ISA-tools/graph2tab for details.
Presentation given to my group at EBI, on Feb 2, 2012.
Building Linked Data for the EBI RDF Platform and biomedical samples: what we have learned and delivered during the Biomedbridges project. Original @ https://prezi.com/vxox0pgra6d7/biosd-linked-data-lessons-learned/
myequivalents is a system to manage cross-references between entities that can be identified by pairs composed of a service name (e.g., EBI's ArrayExpress, Wikipedia) and an accession (e.g., E-MEXP-2514, Barack_Obama). For those familiar with the Semantic Web, we plan to support identification of entities via URIs and the owl:sameAs property. For those who already know MIRIAM and identifiers.org, myequivalents is more general than them and we plan to support these services in future.
A few notes here about the UK Ontology Network Meeting (http://dream.inf.ed.ac.uk/events/ukont-13/2013_workshop_program.html) I've attended on 11/Apr/2013.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Toxic effects of heavy metals : Lead and Arsenicsanjana502982
Heavy metals are naturally occuring metallic chemical elements that have relatively high density, and are toxic at even low concentrations. All toxic metals are termed as heavy metals irrespective of their atomic mass and density, eg. arsenic, lead, mercury, cadmium, thallium, chromium, etc.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
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.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.