This document presents an international accord on open data signed by ICSU, IAP, ISSC, and TWAS. It outlines the opportunities of open data in today's data-rich world. It defines open data principles and responsibilities for various stakeholders, including scientists, research institutions, publishers, funding agencies, and professional organizations. It emphasizes making data discoverable, accessible, intelligible, assessable, and usable. Overall it promotes open data as the default approach while allowing exceptions on a case-by-case basis for privacy, safety, security, and commercial interests.
Presentation at
CODESRIA-UNESCO –CLACSO Panel: Strengthening Scholarly Community Led open access publishing in the Global South
CODESRIA Conference on Electronic Publishing and Dissemination
CODESRIA-Council for the Development of Social Science Research in Africa
Dakar, Senegal, March 31st., 2016
Presentation by CLACSO, academic network of 616 social science research institutions in 47 countries, at OAI10 (CERN-UNIGE, Geneva, 21-23 June 2017), about the world landscape of repositories and regional repositories networks, its achievements and challenges, and the importance of open access being managed as a commons by the scholarly community
CLACSO´s invited presentation, by Dr.Pablo Vommaro (CLACSO-University of Buenos Aires UBA), at UNESCO NGO´s International Conference of Non-Governmental Organizations. Paris, UNESCO, 12-14 December 2016
Presentation at: Webinar Open Book Metadata. OASPA-Open Access Scholarly Publishing Association. 10 February 2021.
Video of webinar: https://oaspa.org/webinar-open-book-metadata/
Presentation at COAR-SPARC conference “Connecting research, bridging communities, opening scholarship. University of Porto, Portugal, April 15-16, 2015
https://www.coar-repositories.org/news-media/coar-sparc-conference-2015-connecting-research-results-bridging-communities-opening-scholarship/
Presentation at COAR-SPARC Conference “Connecting research, bridging communities, opening scholarship". University of Porto, Portugal, April 15-16, 2015
sparc.arl.org/events/joint-coar-sparc-conference
Presentation at
CODESRIA-UNESCO –CLACSO Panel: Strengthening Scholarly Community Led open access publishing in the Global South
CODESRIA Conference on Electronic Publishing and Dissemination
CODESRIA-Council for the Development of Social Science Research in Africa
Dakar, Senegal, March 31st., 2016
Presentation by CLACSO, academic network of 616 social science research institutions in 47 countries, at OAI10 (CERN-UNIGE, Geneva, 21-23 June 2017), about the world landscape of repositories and regional repositories networks, its achievements and challenges, and the importance of open access being managed as a commons by the scholarly community
CLACSO´s invited presentation, by Dr.Pablo Vommaro (CLACSO-University of Buenos Aires UBA), at UNESCO NGO´s International Conference of Non-Governmental Organizations. Paris, UNESCO, 12-14 December 2016
Presentation at: Webinar Open Book Metadata. OASPA-Open Access Scholarly Publishing Association. 10 February 2021.
Video of webinar: https://oaspa.org/webinar-open-book-metadata/
Presentation at COAR-SPARC conference “Connecting research, bridging communities, opening scholarship. University of Porto, Portugal, April 15-16, 2015
https://www.coar-repositories.org/news-media/coar-sparc-conference-2015-connecting-research-results-bridging-communities-opening-scholarship/
Presentation at COAR-SPARC Conference “Connecting research, bridging communities, opening scholarship". University of Porto, Portugal, April 15-16, 2015
sparc.arl.org/events/joint-coar-sparc-conference
Presentation at: Open Access to HSS research: Perspectives from Latin America and United Kingdom. Azim Premji University, Bengaluru, India, 17 Febrero 2021.
Video of presentation: https://www.youtube.com/watch?v=uAJIY74o3yA&ab_channel=AzimPremjiUniversity
Presentation at webinar: Equity and inclusion: community-owned infrastructures for open science. Organized by: Confederation of Open Access Repositories (COAR), European Open Access Infrastructure (OpenAIRE) y Electronic Information for Libraries (EIFL). 21 October 2020.
Video of webinar: https://www.youtube.com/watch?v=OJifBtuBlRM&feature=emb_imp_woyt&ab_channel=OpenAIRE_eu
Program: https://www.openaire.eu/item/equity-and-inclusion-community-owned-infrastructures-for-open-science
This presentation was provided by Kieth Webster of Carnegie Mellon University, during the NISO event "No More Big Deal? Picking and Choosing Titles for Use," held on July 6, 2020.
Presentation from CLACSO (Dominique Babini and Laura Rovelli) at the Arab Council for the Social Sciences-ACSS, 10° Anniversary webinar "Knowledge for the Public Good", 10th. April 2021. http://www.theacss.org/pages/webinar_three
Presentation at the 2nd. Open Science Conference-From tackling the pandemic to addressing climate change. Virtual Conference, 21-23 July 2021. https://www.un.org/en/library/OS21
Presentation from Dominique Babini (CLACSO) and Arianna Becerril (Redalyc-AmeliCA-UAEM) at webinar "Open Access 2020 Equity and inclusion in global open access scholarly communications" DST-Center for Policy Research, Indian Institute of Science, 24 October 2020
Video of webinar: https://www.youtube.com/watch?v=cmRMKIpRdsQ&feature=emb_logo&ab_channel=DST-CentreforPolicyResearch%2CIISc%2CBangalore
Program: https://dstcpriisc.org/2020/10/16/equity-and-inclusion-in-global-open-access-scholarly-communications/
This presentation was provided by Nancy Davenport of American University during the NISO event, "The Library of the Future: Inside & Out", held on December 12, 2018.
PIDs, Data and Software: How Libraries Can Support Researchers in an Evolving...Sarah Anna Stewart
Presentation given at the M25 Consortium of Academic Libraries, CPD25 Event on 'The Role of the Library in Supporting Research'. Provides an introduction to data, software and PIDs and a brief look at how libraries can enable researchers to gain impact and credit for their research data and software.
Transparency and reproducibility in researchLouise Corti
Talk given at the ESS Summer School: An introduction to using big data in the social sciences, 20-24 July 2020, University of Essex, Colchester, UK.
In the morning we look at publishing and sharing data and the importance of research replication, code sharing, examining what methodological issues peer reviewers might look for in a published paper using big data. An increasing number of journals in the sciences and social sciences expect a high degree of transparency and knowing how best to publish high quality raw (or processed data), methodology and code is a useful skill. We show how ‘data papers’ help to elucidate how datasets were constructed, compiled and processed, and help to showcase the value of data beyond the original research.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
The Challenges of Making Data Travel, by Sabina LeonelliLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Sabina Leonelli, Exeter Centre for the Study of Life Sciences (Egenis) & Department of Sociology, Philosophy and Anthropology, University of Exeter
Presentation at: Open Access to HSS research: Perspectives from Latin America and United Kingdom. Azim Premji University, Bengaluru, India, 17 Febrero 2021.
Video of presentation: https://www.youtube.com/watch?v=uAJIY74o3yA&ab_channel=AzimPremjiUniversity
Presentation at webinar: Equity and inclusion: community-owned infrastructures for open science. Organized by: Confederation of Open Access Repositories (COAR), European Open Access Infrastructure (OpenAIRE) y Electronic Information for Libraries (EIFL). 21 October 2020.
Video of webinar: https://www.youtube.com/watch?v=OJifBtuBlRM&feature=emb_imp_woyt&ab_channel=OpenAIRE_eu
Program: https://www.openaire.eu/item/equity-and-inclusion-community-owned-infrastructures-for-open-science
This presentation was provided by Kieth Webster of Carnegie Mellon University, during the NISO event "No More Big Deal? Picking and Choosing Titles for Use," held on July 6, 2020.
Presentation from CLACSO (Dominique Babini and Laura Rovelli) at the Arab Council for the Social Sciences-ACSS, 10° Anniversary webinar "Knowledge for the Public Good", 10th. April 2021. http://www.theacss.org/pages/webinar_three
Presentation at the 2nd. Open Science Conference-From tackling the pandemic to addressing climate change. Virtual Conference, 21-23 July 2021. https://www.un.org/en/library/OS21
Presentation from Dominique Babini (CLACSO) and Arianna Becerril (Redalyc-AmeliCA-UAEM) at webinar "Open Access 2020 Equity and inclusion in global open access scholarly communications" DST-Center for Policy Research, Indian Institute of Science, 24 October 2020
Video of webinar: https://www.youtube.com/watch?v=cmRMKIpRdsQ&feature=emb_logo&ab_channel=DST-CentreforPolicyResearch%2CIISc%2CBangalore
Program: https://dstcpriisc.org/2020/10/16/equity-and-inclusion-in-global-open-access-scholarly-communications/
This presentation was provided by Nancy Davenport of American University during the NISO event, "The Library of the Future: Inside & Out", held on December 12, 2018.
PIDs, Data and Software: How Libraries Can Support Researchers in an Evolving...Sarah Anna Stewart
Presentation given at the M25 Consortium of Academic Libraries, CPD25 Event on 'The Role of the Library in Supporting Research'. Provides an introduction to data, software and PIDs and a brief look at how libraries can enable researchers to gain impact and credit for their research data and software.
Transparency and reproducibility in researchLouise Corti
Talk given at the ESS Summer School: An introduction to using big data in the social sciences, 20-24 July 2020, University of Essex, Colchester, UK.
In the morning we look at publishing and sharing data and the importance of research replication, code sharing, examining what methodological issues peer reviewers might look for in a published paper using big data. An increasing number of journals in the sciences and social sciences expect a high degree of transparency and knowing how best to publish high quality raw (or processed data), methodology and code is a useful skill. We show how ‘data papers’ help to elucidate how datasets were constructed, compiled and processed, and help to showcase the value of data beyond the original research.
An introduction to the FAIR principles and a discussion of key issues that must be addressed to ensure data is findable, accessible, interoperable and re-usable. The session explored the role of the CDISC and DDI standards for addressing these issues.
Presented by Gareth Knight at the ADMIT Network conference, organised by the Association for Data Management in the Tropics, in Antwerp, Belgium on December 1st 2015.
The Challenges of Making Data Travel, by Sabina LeonelliLEARN Project
1st LEARN Workshop. Embedding Research Data as part of the research cycle. 29 Jan 2016. Presentation by Sabina Leonelli, Exeter Centre for the Study of Life Sciences (Egenis) & Department of Sociology, Philosophy and Anthropology, University of Exeter
Presentation slides on Open Science and research reproducibility. Presented by Gareth Knight (LSHTM Research Data Manager) on 18th September 2018, as part of an Open Science event for LSHTM Week 2018.
dkNET Office Hours: NIH Data Management and Sharing Mandate 05/03/2024dkNET
Presenter: Jeffrey Grethe, PhD, Principal Investigator of NIDDK Information Network (dkNET), Center for Research in Biological Systems, University of California San Diego
For all proposals submitted on/after January 25 2023, NIH requires the sharing of data from all NIH funded studies. Do you have appropriate data management practices and sharing plans in place to meet these requirements? Have questions or need some help? Join the dkNET office hours to learn about NIH’s policy (NOT-OD-21-013) and resources that could help.
*Previous Office Hours Slides and Recording: https://dknet.org/rin/research-data-management
Upcoming Webinars Schedule: https://dknet.org/about/webinar
Turning FAIR into Reality: Briefing on the EC’s report on FAIR datadri_ireland
DRI Director Natalie Harrower, a member of the European Commission's Expert Group on FAIR (Findable, Accessible, Interoperable and Re-usable) data, delivered a lunchtime briefing on the recently published 'Turning FAIR into Reality' report on Tuesday 26 February in the Royal Irish Academy, Dublin.
In 2016 the FAIR Data Principles were developed to support the position that effective research data management is ‘not a goal in itself but rather is the key conduit leading to knowledge discovery and innovation’. The new publication is both a report and an action plan for turning FAIR into reality. It offers a survey and analysis of what is needed to implement FAIR and it provides a set of concrete recommendations and actions for stakeholders in Europe and beyond.
The briefing provided an overview of the contents of the report, which include the principles of FAIR, as well as the elements required to implement FAIR data.
David Van Enckevort - FAIR sample and data access DataSciSIG
David van Enckevort from the University of Groningen describes FAIR Sample and Data Access in Biobanking and Biorepositories.
This talk was sponsored by the NIH Data Science Special Interest Group and part of a webinar panel on June 23, 2017 on Global Biobanking and Access to Specimens.
This slide deck provides an overview and resources to respond to the OSTP memo with the subject: Increasing Access to the Results of Federally Funded Scientific Research issued by John P. Holdren in February 2013. It provides resources and information agencies, foundations, and research projects can use to assemble achieve public access to scientific data in digital formats.
Meeting Federal Research Requirements for Data Management Plans, Public Acces...ICPSR
These slides cover evolving federal research requirements for sharing scientific data. Provided are updates on federal agency responses to the 2013 OSTP memo, guidance on data management plans, resources for data management and curation training for staff/researchers, and tips for evaluating public data-sharing services. ICPSR's public data-sharing service, openICPSR, is also presented. Recording of this presentation is here: https://www.youtube.com/watch?v=2_erMkASSv4&feature=youtu.be
Similar to Open data in a big data world Accord (ICSU-IAP-ISSC-TWAS) (20)
Presentation CLACSO au 89° Congres ACFAS, Canada, 13 May 2022.
Session:
Diffusion des connaissances, anglicisation et libre accès : perspectives internationales
Colloque 3:
Entre anglicisation de la recherche et libre accès : imaginer l’avenir des revues en sciences humaines et sociales
Présidée par Vincent Larivière (Université de Montréal)
https://www.acfas.ca/evenements/congres/programme/89/enjeux-recherche/3/c
Presentación de CLACSO-FOLEC (Rovelli-Babini) en Global Research Council (GRC), Americas Regional Meeting side event. 3 diciembre 2021. https://fapesp.br/files/upload/15191/program3011.pdf
Presentación CLACSO (Dominique Babini y Laura Rovelli) en Open and Inclusive Access to Research (OIAR)-Acceso Abierto e Inclusivo a la investigación. 8-11 noviembre 2021.
http://openandinclusiveresearch.org/programme/
Reflexiones desde América Latina sobre el ecosistema de acceso abierto en transición hacia prácticas de ciencia abierta. Presentación Babini-Rovelli en: Seminario Internacional Conocimiento Abierto. ANID, Ministerio de Ciencia, Chile. 26-27 octubre 2021. https://www.anid.cl/blog/2021/10/14/conocimiento-abierto/
Presentación en Ciclo de Diálogos MECILA / CLACSO: Desafíos de la conviavilidad: medialidades y desigualdades en tiempos de pandemia. Primer encuentro: Medialidades hoy: circulación y apropiación del conocimiento en América Latina. 10 noviembre, 2020
https://www.clacso.org/actividad/ciclo-de-dialogos-mecila-clacso-medialidades-desigualdades-y-desafios-a-los-conocimientos-en-tiempos-de-pandemia-medialidades-hoy-circulacion-y-apropiacion-del-conocimiento-en-america-latina/
Video: https://www.youtube.com/watch?v=sQ1xtD0CXi4&feature=emb_rel_pause&ab_channel=CLACSOTV
Presentación en evento:
La agenda del Acceso y la Ciencia Abiertos en la crisis pandémica: avances y desengaños
III Foro Virtual - 5 y 6 de agosto 2020
Dirección General de Bibliotecas y Servicios Digitales de Información (DGBSDI)
UNAM-Universidad Nacional Autónoma de México
Presentación en evento virtual "La Difusión de las Ciencias Sociales en la Argentina-50 años de la Revista Realidad Económica". Buenos Aires, IADE, 3 diciembre 2020
http://www.iade.org.ar/actividades/encuentro-de-revistas-la-difusion-de-las-ciencias-sociales-en-la-argentina
Presentación en panel de la Videoconferencia para Presentación del Portal de Revistas de la Universidad Nacional de Rosario, Argentina, el 18 de junio de 2020.
Video del panel: https://www.youtube.com/watch?v=OAOJKuywMPw
Prepared for:
Colloque International Science Ouverte au Sud-Enjeux et Perspectives pour une Nouvelle Dynamique
Université Cheikh Anta Diop, Dakar, Senegal
23-25 Octobre 2019
VIDEO of presentation: Vers un écosystème mondial de communications scientifiques inclusif, non-commercial, dirigée collaborativement par la communauté - contributions depuis l'Amérique latine
VIDEO: https://youtu.be/cPWIwX5LtCU
Presentado en CRECS 2019
9ª Conferencia internacional sobre revistas científicas en Ciencias Sociales y Humanidades
Logroño (España), 23 y 24 de mayo del 2019
Video de la sesión https://www.youtube.com/watch?v=4lZ3gkVvuk8&feature=youtu.be
Programa y acceso a presentaciones: http://www.crecs.info/crecs2019-logro%C3%B1o/
Comentario en la:
Presentación de la Revista AREA N°24 con Dossier sobre “Desnaturalizar y reconstruir. Actores, métodos y saberes invisibilizados”
5 de octubre 2018
Secretaría de Investigación
Facultad de Arquitectura, Diseño y Urbanismo
Universidad de Buenos Aires
Presentación en OpenCon LATAM 2018 el 29 de setiembre 2018 en UMET - Universidad Metropolitana para la Educación y el Trabajo, Buenos Aires, Argentina. Y en JBDU-Jornada sobre la Biblioteca Digital Universitaria 2018 “Reflexiones sobre la biblioteca académica y el contexto” 1 y 2 de noviembre 2018
Universidad Nacional de Quilmes, Bernal, Buenos Aires, Argentina.
Presentación en 3er Congreso Internacional de Editores Redalyc "Construyendo el modelo de publicación académica del sur global" Trujillo, Perú, 16-18 mayo 2018 http://congreso.redalyc.org/ocs/public/congresoEditores/index.html
video de la presentación: https://www.youtube.com/watch?v=kvLA1J6BI1o&feature=youtu.be
Presentación de CLACSO en CRES2018-Conferencia Regional de Educación Superior, Mesa de debate acceso abierto y democratización del conocimiento. Córdoba, Argentina, 12 de junio 2018. http://www.cres2018.org/
World Humanities Conference
CLACSO’s 50th Anniversary Symposium
Panel “The humanities and knowledge as a public good”
University of Liege, Belgium, 7-9 August 2017
Presentation for CLACSO, academic network of 616 social science research institutions in 47 countries, at OAI10 (CERN-UNIGE, Geneva, 21-23 June 2017), about the world landscape of repositories and regional repositories networks, its achievements and challenges, and the importance of open access being managed as a commons by the scholarly community
Presentación invitada en Universidad Buenos Aires, Facultad de Filosofía y Letras, Maestría en Bibliotecología y Ciencia de la Información. Materia: Bibliotecas Digitales Año lectivo: 2015 Profesor: MLIS Paola C. Bongiovani
More from CLACSO-Latin American Council of Social Sciences, Open Access (20)
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
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.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
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 .
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.
Richard's entangled aventures in wonderlandRichard 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.
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.
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.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
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.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...
Open data in a big data world Accord (ICSU-IAP-ISSC-TWAS)
1. .
An international accord
(2015):
ICSU - International Council
for Science
IAP - The InterAcademy
Partnership
ISSC - International Social
Science Council
TWAS - The World
Academy of Sciences
.
2. scientific opportunities of a data-rich world
• capacity to acquire, store, manipulate and instantaneously
transmit vast and complex data volumes
• numerous datasets can be semantically linked to create
deeper meaning
• grasping these opportunities poses serious challenges to the
way science is done and organized
Open data are the common, enabling threads
Effective open data can only be realised if there is systemic
action at personal, disciplinary, national and international levels
3. definition of open data
Data must be “intelligently open”:
• Discoverable – a web search can readily reveal their
existence
• Accessible – the data can be electronically imported
into or accessed by a computer
• Intelligible – background information to make clear the
relevance of the data to the specific issue under
investigation
• Assessable – users must be able to assess issues such
as the competence/interests of the data producers
• Usable – adequate metadata + the relevant code when
computation has been used to create derived data
4. application of principles of open research data
is responsibility of
scientists
research institutions and universities
publishers
funding agencies
professional associations, scholarly societies and
academies
libraries, archives and repositories
national responsibilities
international responsibilities
5. The principles of Open Data
Responsibilities of publicly funded scientists
• make research data openly available in ways that
permit reuse
• permit the logic of the link between data and claim
to be rigorously scrutinised and the validity of the
data to be tested by replication of experiments or
observations
• data deposited in trusted repositories
reusable data
6. Deposit data in your institutional repository + search for data repositories in ww.re3data.org
(1.400) and www.opendoar.org (153)
ww.re3data.org
7. The principles of Open Data
Responsibilities of research institutions and universities
• create a supportive environment for open data. This
includes the provision of training in data management,
preservation of data, technical support, including library
and data management services
• Institutions that employ scientists and bodies that fund
them should develop incentives and criteria for career
advancement for those involved in open data processes
mobilise data-intensive capacities
8. The principles of Open Data
Responsibilities of publishers
• make data available to reviewers during the review process
• require intelligently open access to the data concurrently with
the publication which uses them
• require the full referencing and citation of these data
• make the scientific record available for subsequent analysis
through the open provision of metadata and open access for
text and data mining
9. The principles of Open Data
Responsibilities of funding agencies
• regard the costs of open data processes in a research project to be
an intrinsic part of the cost of doing the research
• provide adequate resources and policies for long-term sustainability
of infrastructure and repositories
national open data policy
• Institutions that employ scientists and bodies that fund them
should develop incentives and criteria for career advancement for
those involved in open data processes
• Assessment of research impact, particularly any involving citation
metrics, should take due account of the contribution of data
creators
10. The principles of Open Data
Responsibilities of professional associations, scholarly
societies and academies
should develop guidelines and policies for
open data
and
promote the opportunities they offer in ways that
reflect the epistemic norms and practices of their
members.
11. The principles of Open Data
Responsibilities of libraries, archives and repositories
development and provision of services and technical
standards for data to ensure that
• data are available to those who wish to use them
and that
• data are accessible over the long term
12. The boundaries of openness
Openness should be the default position for scientific data .
Exceptions should be applied on a case-by-case basis:
Privacy and confidentiality
Safety and security
Commercial interests
Exceptions applied on a case-by-case basis
13. Enabling practices
• Citation and provenance
When, in scholarly publications, researchers use data created by others, those
data should be cited with reference to their originator, to their provenance
and to a permanent digital identifier. .
• Interoperability
Both research data, and the metadata which allows them to be assessed and
reused, should be interoperable to the greatest degree possible
• Non-restrictive reuse
Research data labelled as reusable by means of a rights waiver or non-
restrictive licence
• Linkability
Open data linked with other data based on their content and context in order
to maximise their semantic value
14.
15. ICSU-IAP-ISSC-TWAS Accord
www.icsu.org/science-international/accord
This document was prepared by an ICSU-IAP-
ISSC-TWAS working group of:
• Geoffrey Boulton, University of Edinburgh
and President of CODATA, Working Group
Chair
• Simon Hodson, Executive Director CODATA
(ICSU representative)
• Dominique Babini, University of Buenos
Aires and CLACSO (ISSC representative)
• Jianhui Li, Chinese Academy of Sciences,
CNIC (IAP representative)
• Tshilidzi Marwala, University of
Johannesburg (TWAS representative)
• Maria G. N. Musoke, Makerere University,
Uganda (IAP representative)
• Paul F. Uhlir, Scholar, US National Academy
of Sciences (IAP representative); Independent
Consultant, Data Policy and Management
• Sally Wyatt, Maastricht University, &
eHumanities, KNAW (ISSC representative)
• .
Editor's Notes
This accord on “Open data in a big data world” adds the distinctive voice of the scientific community to those of governments and inter-governmental bodies that have made the case for open data as a fundamental pre-requisite in maintaining the rigour of scientific inquiry and maximising public benefit from the data revolution in both developed and developing countries.
The accord makes the normative assertion that publicly funded research should be undertaken in a way that creates maximum public benefit. It argues that the open release of data is the optimal route by which this is achieved.
The accord identifies the opportunities and challenges of the data revolution as today’s predominant issue for global science policy.
It proposes fundamental principles that should be adopted in responding to them.
There are many areas of research where such capacities are deeply relevant: in weather and climate forecasting; in understanding the workings of the brain; in the behaviour of the global economy; in evaluating agricultural productivity; in demographic forecasts; in unravelling histories; and in many of contemporary global challenges such as those of environmental change, infectious disease and mass migration that require combined insights and data from many disciplines, are only examples of possible applications
A changing environment. E.g.: In 2003 scientists declared the mapping of the human genome complete. It took over 10 years and cost $1billion – today it takes mere days and a small fraction of the cost ($1000)
Governments hold data that are of great value to the scientific enterprise if made open, particularly in the social sciences
In this context of data-rich world , the following fundamental principles for open research data have been agreed by four top-level representatives of international science
Simply making data accessible is not enough. Data must be “intelligently open” , meaning that they can be thoroughly scrutinised and appropriately re-used. The following criteria should be satisfied for open data
If data, meta-data and the code used in any manipulations are not available for scrutiny, published work, whether right or wrong, cannot be subject to an adequate test of replication
A growing number of researchers share their data from the start of their research projects, both to receive comments from peers and to engage in open collaborationStrong processes of open data sharing have developed in areas such as linguistics, bioinformatics and chemical crystallography. In human palaeogenetics, it appears that open data sharing is almost universal (>97%),
e.g.of international responsibilities: CODATA in collaboration with the Research Data Alliance (RDA) organize worldwide training activities
Publicly funded scientists have a responsibility to contribute to the public good through the creation and communication of new knowledge, of which associated data are intrinsic parts. They should make such data openly available to others as soon as possible after their production, deposited in repositories in ways that permit them to be re-used and re-purposed.
When a paper making a scientific claim is published, it is essential that the evidentiary data, the related metadata that permit their re-analysis, and the codes used in computer manipulation are made concurrently open to scrutiny to ensure that the vital process of self-correction is maintained. Recent demonstrations in several disciplines of high rates of non-reproducibility of results of published papers emphasise the crucial need to re-invigorate open data processes for a big data world. Openness is not however enough. Data must be intelligently open, meaning that they should be: discoverable, accessible, intelligible, assessable and (re-)usable.
Recent attempts to replicate systematically the results of series of highly regarded published papers were successful in only a low percentage, for example, pre-clinical oncology (53 papers, only 11% replicable) , social psychology (100 papers, only 39% replicable) and economics (67 papers, only 33% replicable). The reasons adduced for these failures included falsification of data, invalid statistical reasoning and absent or incompleteness of the data or metadata
Deposit your data your institutional repository and/or in data repositories (ww.re3data.org with 1.400 data repositories in february 2016) and/or general repositories (www.opendoar.org with 153 repositories reporting datasets in February 2016)
Exceptions to open data should be limited to issues of privacy, safety, security and to commercial use in the public interest
Research Institutions have a responsibility to promote and enable open data processes by funding infrastructure and services, and by stimulating research on fundamentals of data science; and accepting that the cost of open data is an inseparable cost of doing research.
Publishers of research papers that present scientific claims should require the evidential data to be concurrently made intelligently open in a trusted data repository. It is a fundamental principle of transparency and reproducibility in research that the data underlying a claim should be accessible for testing
Funders of Research have a responsibility to promote and enable open data processes by funding relevant infrastructure; By providing dedicated funding lines to support the reuse of open data; by stimulating research on fundamentals of data science; and by creating incentives for research performing institutions that help them to exercise their responsibilities and accepting that the cost of open data is an inseparable cost of doing research.
practices that ensure efficient operation of a national open data system that is also consistent with international standards
In this agreement on open data have participated the international networks ICSU, ISSC, The InterAcademy Partnership (IAP) which is the global network of science academies in countries around the world, and The World Academy of Sciences (TWAS), that brings together scientists from 70 countries
National Academies and Learned Societies are distinctive in speaking to scientists directly and influencing “bottom-up” initiatives by expressing the principles and priorities of research in their specific fields. They should develop guidelines and policies for open data and promote the opportunities they offer in ways that reflect the epistemic norms and practices of their members.
Institutional Libraries have a continuing role to collect, to organize, to preserve knowledge, and to make it accessible. Many are now adapting to the technological change from paper to digital formats and to the open data management issues highlighted by this accord, but it is a major and difficult transition that requires sustained effort
Openness should be the default position for scientific data although there are exceptions
Privacy and confidentiality: The sharing of datasets containing personal information is of critical importance for research in many areas of the medical and social sciences, but poses challenges for information governance and the protection of confidentiality. Complete anonymisation of personal records in databases is impossible. A way of dealing with such issues is through what are sometimes called “safe havens”, where data are kept physically secure, and only made available to bona fide researchers, with legal sanctions against unauthorised release. In some cases, consent for data release can be appropriate.
Careful scrutiny of the boundaries of openness is important where research could in principle be misused to threaten security, public safety or health.
There can be a public interest in the commercialisation of scientific discovery where that is the route to the greatest public benefit in the national jurisdiction in which the discovery is made.
as it is difficult to draw sharp, general boundaries for each of these cases, they should be applied with discrimination on a case-by-case basis because there have been many major discoveries where suppression of data release or the privatisation of knowledge would have been highly retrograde, such as the discovery of electricity, the human genetic code, the internet etc.
citation is an important component of the system of academic recognition and reward. Therefore, integrating the practice of data citation must be seen as an important step in providing incentives for ‘data sharing´
Data should be released into the public domain as soon as possible after their creation. Data that underpin a scientific claim should be released into the public domain concurrently with the publication of the claim. Some funders allow public release to be delayed for precisely limited periods.
A permanent digital identifier is particularly important when dynamically created subsets or specific versions of time-series datasets may be at issue
Additional metadata is necessary to determine the provenance of the data and to understand the circumstances in which they were created and in what way they may be reused. Standards exist in most research disciplines for the way in which data should be described and the circumstances of their creation reported.
For science there is an unprecedented capacity offered by text and data mining (TDM) to harvest the cumulative scientific knowledge of a phenomenon from already published work.The historical record of scientific discovery and analysis published in scientific journals should be accessible to text and data mining (TDM). At the very least, this should be at no additional cost by scientists from journals to which their institution already subscribes.
Interoperability is a property of a product or system, whose interfaces are completely understood, to work with other products or systems, present or future, without any restricted access or implementation. Interoperability is an attribute that greatly facilitates usability of research data
Non-restrictive reuse:
Different ministries or research agencies may adopt a policy that allows research data produced through their funding to be placed in the public domain.
In the absence of a broad law that enables the re-use, re-dissemination and legal interoperability of data, a voluntary rights waiver or a non-restrictive, “common-use” licence can be used by the rights holder (see: www.creativecommons.org).
If research data are not already in the public domain, they should be labelled as reusable by means of a rights waiver or non-restrictive licence that makes it clear that the data may be re-used with no more arduous requirement than that of acknowledging the producer. The RDA-CODATA Interest Group on Legal Interoperability of Research Data has produced Principles and Implementation Guidelines
The infrastructure requirements for an efficient open data environment. Technology is only a part. The vital, submerged elements relate to processes, organisation and personal skills, motivation and ethos.
Actions that encourage appropriate open data practices fall into three categories–those that encourage researchers to make data open, those that encourage the use of open data, and those that discourage closed data practices. The potential roles of key actors need to be considered– research funders, institutions, publishers and researchers themselves. These actors are the key elements of the research community. They need to work together to ensure that data are considered legitimate, citable products of research; with data citations being accorded the same importance in the scholarly record as citations of other research objects, such as publications