The document discusses the transition to open access and FAIR (Findable, Accessible, Interoperable, Reusable) research data. It outlines the European Commission's efforts over the past 10 years to promote open access to publications and research data resulting from publicly funded research. The document notes that Horizon 2020 now requires open access by default for research data and promotes FAIR data management through mandatory Data Management Plans. Upcoming steps include further developing the European Open Science Cloud to enable access to and sharing of FAIR research data across Europe.
Connecting the dots - e-Infra services for open scienceOpenAIRE
Starting from Open access towards services for open science, we present OpenAIRE, OpenMinTeD and OpenUP, three EU projects that build services to facilitate and accelerate open science.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
Connecting the dots - e-Infra services for open scienceOpenAIRE
Starting from Open access towards services for open science, we present OpenAIRE, OpenMinTeD and OpenUP, three EU projects that build services to facilitate and accelerate open science.
Big Data Europe SC6 WS 3: Where we are and are going for Big Data in OpenScie...BigData_Europe
Where we are and are going for Big Data in OpenScience
Keynote talk at the Big Data Europe SC6 Workshop on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017: The perspective of European official statistics by Fernando Reis, Task-Force Big Data, European Commission (Eurostat).
OpenAIRE guidelines and broker service for repository managers - OpenAIRE #OA...OpenAIRE
Presentation by Pedro Principe and Paolo Manghi at the OpenAIRE Open Access week webinar. Friday October 28, 2016. Webinar on Openaire compatibility guidelines and the dashboard for Repository Managers, with Pedro Principe (University of Minho) and Paolo Manghi (CNR/ISTI).
Alma Swan - PASTEUR4OA: Policy alignment and effectivenessOpenAIRE
Presentation given as part of OpenAIRE Webinar "Policies for Open Science: webinar for research managers and policy makers", Open Access Week 2016 (27.10.2016)
OpenAIRE webinar on Open Access in H2020 (OAW2016)OpenAIRE
OpenAIRE Webinar for project coordinators and researchers on Open Access to publications in H2020 - By Eloy Rodrigues and Pedro Principe (University of Minho, OpenAIRE Helpdesk & Training managers). Open Access Week 2016 initiatives.
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
Open science as roadmap to better data science researchBeth Plale
Open science is a principle -- of openness -- applied to scientific research and its products which include data and software. Its objective is to accelerate the dissemination of fundamental research results that will “advance the frontiers of knowledge and help ensure the nation’s future prosperity.” Open science has both socio- and technical- components to it. It urges from scientists more attention to research processes, more thought to subsequent uses of data, and more thought to the reproducibility and replicability of one’s work. It urges computational infrastructure to be more responsive to reproducibility. It urges science communities to value their data gems. As it is rare for data science research to not involve actual data nor software, and at times it requires large amounts of both, the principles of open science are particularly relevant to data science. In this talk I discuss open science in data science and show that open science equates to good science that in the end benefits us all.
OpenAIRE-COAR conference 2014: Open Access in H2020, by Anni Hellman - Europe...OpenAIRE
Presentation at the OpenAIRE-COAR Conference: "Open Access Movement to Reality: Putting the Pieces Together", Athens - May 21-22, 2014.
Open Access in H2020, by Anni Hellman - European Commission.
OpenAIRE guidelines and broker service for repository managers - OpenAIRE #OA...OpenAIRE
Presentation by Pedro Principe and Paolo Manghi at the OpenAIRE Open Access week webinar. Friday October 28, 2016. Webinar on Openaire compatibility guidelines and the dashboard for Repository Managers, with Pedro Principe (University of Minho) and Paolo Manghi (CNR/ISTI).
Alma Swan - PASTEUR4OA: Policy alignment and effectivenessOpenAIRE
Presentation given as part of OpenAIRE Webinar "Policies for Open Science: webinar for research managers and policy makers", Open Access Week 2016 (27.10.2016)
OpenAIRE webinar on Open Access in H2020 (OAW2016)OpenAIRE
OpenAIRE Webinar for project coordinators and researchers on Open Access to publications in H2020 - By Eloy Rodrigues and Pedro Principe (University of Minho, OpenAIRE Helpdesk & Training managers). Open Access Week 2016 initiatives.
Big Data Europe SC6 WS 3: Ron Dekker, Director CESSDA European Open Science A...BigData_Europe
Slides for keynote talk at the Big Data Europe workshop nr 3 on 11.9.2017 in Amsterdam co-located with SEMANTiCS2017 conference by Ron Dekker, Director CESSDA: European Open Science Agenda: where we are and where we are going?
Open science as roadmap to better data science researchBeth Plale
Open science is a principle -- of openness -- applied to scientific research and its products which include data and software. Its objective is to accelerate the dissemination of fundamental research results that will “advance the frontiers of knowledge and help ensure the nation’s future prosperity.” Open science has both socio- and technical- components to it. It urges from scientists more attention to research processes, more thought to subsequent uses of data, and more thought to the reproducibility and replicability of one’s work. It urges computational infrastructure to be more responsive to reproducibility. It urges science communities to value their data gems. As it is rare for data science research to not involve actual data nor software, and at times it requires large amounts of both, the principles of open science are particularly relevant to data science. In this talk I discuss open science in data science and show that open science equates to good science that in the end benefits us all.
OpenAIRE-COAR conference 2014: Open Access in H2020, by Anni Hellman - Europe...OpenAIRE
Presentation at the OpenAIRE-COAR Conference: "Open Access Movement to Reality: Putting the Pieces Together", Athens - May 21-22, 2014.
Open Access in H2020, by Anni Hellman - European Commission.
“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015, conference organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015
Open Research Data: Present and planned EC Policy, Jean-Claude Burgelman impl...Platforma Otwartej Nauki
“Open Research Data: Implications for Science and Society”, Warsaw, Poland, May 28–29, 2015. The conference was organized by the Open Science Platform — an initiative of the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw. pon.edu.pl @OpenSciPlatform #ORD2015
The section provides an overview of the open science requirements and how to comply with them stipulated by selected funders and organizations: H2020 & ERC, FWO and Belspo by Emilie Hermans
Vortrag im Rahmen der EERA-Session: Open Science and Educational Research? Inclusion and Exclusion at the European Open Science Cloud; am 5. September 2018 in Bolzano (Italien).
European Commission
DG Research and Innovation
RTD.A2. Open Data Policy and Science Cloud
Katarzyna Szkuta
A presentation given on the Horizon 2020 open data pilot as part of a series of OpenAIRE webinars for Open Access week 2014 - http://www.fosteropenscience.eu/event/openaire-webinars-during-oa-week-2014
The Horizon 2020 Open Data Pilot - OpenAIRE webinar (Oct. 21 2014) by Sarah J...OpenAIRE
Sarah Jones (HATII, Digital Curation Center) will provide more information on the Open Research Data Pilot in H2020: who should participate and how to comply (in collaboration with FOSTER)
Date: Tuesday, October 21 2014
Presentation given to EC project officers as part of workshops run by the FOSTER (foster open science) project. The presentation covers the Horizon 2020 open data pilot.
OpenAIRE Content Providers Community Call, November 4th, 2020
This call was focused on the PROVIDE future developments, functionalities wishlist and PROVIDE service in EOSC.
Was also an opportunity to share the most recent updates and novelties in the OpenAIRE Content Provider Dashboard, and to get feedback from community.
Recordings: https://youtu.be/wY4fOS767Us
Follow the Community activities at https://www.openaire.eu/provide-community-calls
OpenAIRE in the European Open Science Cloud (EOSC)OpenAIRE
Openness is the success factor for EOSC. OpenAIRE has been working in delivering an open access scholarly communication in Europe for the past 10 years and we now present how our work fits into the EOSC core developments
OpenAIRE Content Providers Community Call, October 7th, 2020
This call was focused on the OpenAIRE Broker Service, specifying how the service works to deploy the enrichment events to the Content Providers managers.
Was also an opportunity to share the most recent updates and novelties in the OpenAIRE Content Provider Dashboard, and to get feedback from community.
Recording: https://youtu.be/3sF4B58EGcs
Follow the Community activities at https://www.openaire.eu/provide-community-calls
OpenAIRE Content Providers Community Call, July 1st, 2020
This call was focused on Data Repositories namely the OpenAIRE Research Graph and Data Repositories, the OpenAIRE Content Acquisition Policy, and the Guidelines for Data Archive Managers.
Was also an opportunity to share the most recent updates and novelties in the OpenAIRE Content Provider Dashboard, and to get feedback from community.
Follow the Community activities at https://www.openaire.eu/provide-community-calls
OpenAIRE Content Providers Community Call. May 6th, 2020.
This Call focused the presentation of the new User Interface of Provide Dashboard and the presentation of 4 use cases using the Provide service.
Was also an opportunity to share the most recent updates and novelties in the OpenAIRE Content Provider Dashboard, and to get feedback from community.
Recording available here: https://youtu.be/J4m_ryRxtnY
20200504_OpenAIRE Legal Policy Webinar: GDPR and Sharing DataOpenAIRE
Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200504_Research Data & the GDPR: How Open is Open?OpenAIRE
Presentation by Prodromos Tsiavos (Senior Legal Advisor - ARC/ Director - Onassis Group) as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200504_Data, Data Ownership and Open ScienceOpenAIRE
Presentation by Thomas Margoni (Senior Lecturer in Intellectual Property and Internet Law, Co-director, CREATe, University of Glasgow) as delivered during the OpenAIRE Legal Policy Webinar series on May 4th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200429_Research Data & the GDPR: How Open is Open? (updated version)OpenAIRE
Presentation by Prodromos Tsiavos (Senior Legal Advisor - ARC/ Director - Onassis Group) as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200429_Data, Data Ownership and Open ScienceOpenAIRE
Presentation by Thomas Margoni (Senior Lecturer in Intellectual Property and Internet Law, Co-director, CREATe, University of Glasgow) as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
20200429_OpenAIRE Legal Policy Webinar: GDPR and Sharing DataOpenAIRE
Presentation by Jacques Flores Dourojeanni (Research Data Management Consultant Utrecht University Library), as delivered during the OpenAIRE Legal Policy Webinar series on April 29th 2020.
More information and recordings: https://www.openaire.eu/item/openaire-legal-policy-webinars
COVID-19: Activities, tools, best practice and contact points in GreeceOpenAIRE
Presentation from the webinar organized by the Greek OpenAIRE and RDA Nodes (Athena RC) and Elixir-GR to inform participants of EU and national efforts, in collaboration with the following research organizations: Flemming, CERTH, HEAL-Link, Demokritos, Univ. of Athens (Medical School).
Presentation of the 2nd Content Providers Community Call, targeting the following topics: 1) OpenAIRE Content provider dashboard updates; Main topic: DSpace-CRIS for OpenAIRE: implementation of the CRIS guidelines and beyond; 3) Community questions & comments.
Presentation of the 2nd Content Providers Community Call, targeting the following topics: 1) OpenAIRE Content provider dashboard updates;
2) OpenAIRE aggregation and enrichment processes: specifications and good practices;
3) Community questions & comments.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
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.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
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.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Horizon 2020 Open Research Data Pilot, Jean-Claude Burgelman, DG RTD European Commission (8th OpenAIRE workshop)
1. From vision to action
From open to FAIR data
OpenAIRE workshop - Legal issues in Open Research Data
April 4, Barcelona
Jean-Claude Burgelman
Daniel Spichtinger
DG RTD European Commission
2. 10 years to become open
FP7
OA Green or
Gold+Green
Pilot
H2020
OA Green or
Gold+Green
obligation
& ORD Pilot
H2020
OA Green or
Gold+Green
obligation
& ORD by
default
3. "To increase the circulation and exploitation of knowledge, open access to scientific
publications should be ensured. Furthermore, open access to research data resulting from
publicly funded research under Horizon 2020 should be promoted, taking into account
constraints pertaining to privacy, national security and intellectual property rights
Open access to scientific publications resulting from publicly
funded research under Horizon 2020 shall be ensured [...].
Open access to research data resulting from publicly funded
research under Horizon 2020 shall be promoted. [...]."
Now: Regulation establishing H2020
4. ORD pilot extension: implementation
Extension of limited Open Research Data (ORD) Pilot to all areas of Horizon 2020
whilst retaining its key characteristics:
• Robust opt outs options for IPR, confidentiality/privacy and security reason as well
as if OA runs against the main objective of the project
• Targeted primarily towards data underlying publications (other data as specified in
DMP)
• a Data Management Plan (DMP) is obligatory for projects that do not opt-out
• Costs for open access to research data fully eligible
• Whether projects opt-out or not does not affect the evaluation
General approach: as open as possible, as closed as needed
5. ORD Pilot: opt-out reasons among proposals
Calls in core-areas:
65% stay in
Opt out 35%
Other areas:
Voluntary
opt in 14%
7. Clarifying terminology…
In the past our policy mainly addressed
the 'accessibility' part of FAIR.
• Started off with 'open access to research
data'
• Moved towards open (research) data
with the ORD pilot (which also covered
further aspects)
• We are now seeing openness as one
component of FAIR data and aim to
address all of the FAIR aspects in
Horizon 2020
8. A FAIR DMP has to adress that data are
o 'Findable', i.e. discoverable with metadata, identifiable and locatable by
means of a standard identification mechanism;
o 'Accessible', i.e. always available and obtainable;
o 'Interoperable', i.e. both syntactically parseable and semantically
understandable, allowing data exchange and reuse between
researchers, institutions, organisations or countries; and
o 'Reusable', i.e. sufficiently described and shared with the least restrictive
licences, allowing the widest reuse possible and the least cumbersome
integration with other data sources.
9. FAIR Data Management DMP
o Template DMP (Annex to Guidelines on FAIR Data Management)
Provided as a service, its use is currently optional
o Standard DMP template is light and flexible
Set of questions + summary table
o One DMP per project not per dataset
but mention if there are specific issues for a particular dataset)
o DMP as a living document
Updated as part of periodic evaluation and/or at least at the end of the
project for final reporting
10. Guidelines on FAIR Data Management
• Available here on
the Participant
Portal!
11. Initial DMP experiences
o Additional guidance on data management is needed for all groups of actors in
research projects (researchers, peer reviewers and funder administrators ('project
officers') including roles supporting researchers with data management tasks
(data librarians or IT professionals working in data centres).
o Aspects such as data preservation, IPR or standards are too often not well
developed in the DMPs that have been submitted so far
o Nevertheless research projects with excellent RDM performance are not rare.
Some high quality DMPs from H2020 projects have already been published
online, see
o http://www.dcc.ac.uk/resources/data-management-plans/guidance-examples
Source: REA 2016 assessment of
H2020 Societal Challenge 6
projects.
13. "Europe's final transition must be one from
fragmented data sets to an integrated European
Open Science Cloud. By 2020, we want all
European researchers to be able to deposit,
access and analyse European scientific data
through a European Open Science Cloud."
The Commissioner's vision on EOSC
Speech by Commissioner Carlos Moedas in Amsterdam, NL:
“Open science: share and succeed”, 4 April 2016
= EOSC is about (FAIR) research data
14. Part of DSM strategy (19 April 2016), strong political
support.
o 'Game-changing policy', a 'vision'.
o Commissioners Moedas & Oettinger
o Supported by Pres. Juncker, VP Ansip, Ch. Merkel, LUX
Presidency, NL Presidency, 2 sets of COMPET Council
Conclusions, EP Report on DSM Act, EESC, …
Communication 2016/178 : European Cloud Initiative
15. Governance
Develop roadmap for governance and financing
Create a global level playing field for research data sharing
Widen user-base to public services, Industry and EU-13
(Open data) Infrastructure
Action Plan for scientific data Interoperability (e.g. FAIR)
Connect key EU RI (e.g. ESFRIs)
Consolidate / federate data-infrastructures
Content (open data)
Make Open research data default in H2020
Foster scientific data sharing in MS
Hardware
Infrastructure (CNECT)
High-Performance
Computing
Big-data
storage
High-speed
connectivity
Policy actions foreseen in the COM 2016
FAIR
FAIR
17. o EOSC Summit will include inputs from OSPP, HLEG EOSC, FAIR
expert group, and EOSC Pilot– 12 June 2017
o 'Declaration of intent' and 'Coalition of the willing' will include parts on
FAIR data – end of summer 2017
o Interim governance board of EOSC will need to have FAIR people on
board
o Action Plan for FAIR data Interoperability - Summer 2018
The next practical steps
19. Get more of these
• 1.3 Billion EUR per year
• Benefits identified by the European
Bioinformatics Institute to users and
their funders just by making scientific
information freely available to the
global life science community
• This is equivalent to more than 20
times the direct operational cost of
the Institute
Source: Charles Beagrie Ltd. For EMBL-EBI
20. Define data dynamically to fit open science:
- data
- methods
- algorithms
- SW
in one word: all that is needed (FAIR) to make
science reproducible
21. We should not give in on scientific and independent QUALITY
22. So
lets move FAIR from concept to operational reality
that serves OPEN SCIENCE
(and lets do that asap)
Editor's Notes
Content
1. Open Research Data in Horizon 2020
2. FAIR data management in Horizon 2020
3. FAIR data and the EOSC