The Arabidopsis Information Portal (araport.org) is a resource for the plant genomics research community. The AIP conducts developer workshops to help other labs get involved. This presentation introduces the web site with a case study about contributing new module built around a legacy data set.
Michal Malohlava from H2O.ai talks about the new features in Sparkling Water 2.0 and the future roadmap.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
BDW Chicago 2016 - Jim Scott, Director, Enterprise Strategy & Architecture - ...Big Data Week
For the past 25 years applications have been getting built using an RDBMS with a predefined schema which forces data to conform with a schema on-write. Many people still think that they must use an RDBMS for applications even though records in their datasets have no relation to one another. Additionally, those databases are optimized for transactional use, and data must be exported for analytics purposes. NoSQL technologies have turned that model on its side to deliver groundbreaking performance improvements.
I will walk through a music database with over 100 tables in the schema and show how to convert that model over for use with a NoSQL database. I will show how to handle creating, updating and deleting records, using column families for different types of data (and why).
Michal Malohlava from H2O.ai talks about the new features in Sparkling Water 2.0 and the future roadmap.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
BDW Chicago 2016 - Jim Scott, Director, Enterprise Strategy & Architecture - ...Big Data Week
For the past 25 years applications have been getting built using an RDBMS with a predefined schema which forces data to conform with a schema on-write. Many people still think that they must use an RDBMS for applications even though records in their datasets have no relation to one another. Additionally, those databases are optimized for transactional use, and data must be exported for analytics purposes. NoSQL technologies have turned that model on its side to deliver groundbreaking performance improvements.
I will walk through a music database with over 100 tables in the schema and show how to convert that model over for use with a NoSQL database. I will show how to handle creating, updating and deleting records, using column families for different types of data (and why).
Since the irruption in the market of the NoSQL concept, graph databases have been traditionally designed to be used with Java or C. With some honorable exceptions, there isn't an easy way to manage graph databases from Python. In this talk, I will introduce you some of the tools that you can use today in order to work with those new challenging databases, from our favorite languge, Python.
RDFa: introduction, comparison with microdata and microformats and how to use itJose Luis Lopez Pino
Presentation for the course 'XML and Web Technologies' of the IT4BI Erasmus Mundus Master's Programme. Introduction, motivation, target domain, schema, attributes, comparing RDFa with RDF, comparing RDFa with Microformats, comparing RDFa with Microdata, how to use RDFa to improve websites, how to extract metadata defined with RDFa, GRDDL and a simple exercise.
Apache conbigdata2015 christiantzolov-federated sql on hadoop and beyond- lev...Christian Tzolov
Slides from ApacheCon BigData 2015 HAWQ/GEODE talk: http://sched.co/3zut
In the space of Big Data, two powerful data processing tools compliment each other. Namely HAWQ and Geode. HAWQ is a scalable OLAP SQL-on-Hadoop system, while Geode is OLTP like, in-memory data grid and event processing system. This presentation will show different integration approaches that allow integration and data exchange between HAWQ and Geode. Presentation will walking you through the implementation of the different Integration strategies demonstrating the power of combining various OSS technologies for processing bit and fast data. Presentation will touch upon OSS technologies like HAWQ, Geode, SpringXD, Hadoop and Spring Boot.
SQL on Hadoop: Defining the New Generation of Analytics Databases DataWorks Summit
The analytics and data warehousing industries are in the midst of a major period of transformation. Since the publication of Google?s MapReduce paper, we have witnessed the appearance of Apache Hadoop, followed by the arrival of batch-oriented SQL systems like Apache Hive, and the scramble by established SQL vendors to implement Hadoop connectors. This talk addresses the recent emergence of a new generation of analytic databases inspired by Google Dremel. These databases have been designed with the goal of running real-time SQL natively on Hadoop in a manner that fully exploits the flexibility and performance of the underlying platform. Characterized by features including schema-on-read, support for semi-structured data, and pluggable storage engines, these new systems share important architectural details that distinguish them from the previous generation of analytic databases. In this talk, we will discuss the performance limitations of the connector-based approach employed by many established vendors and explain the long-term significance of Apache Hive?s data model. Then, we will unravel the novel architectural features common to next generation analytic database systems like CitusDB and Impala that make real-time SQL-on-Hadoop feasible. Finally, we will conclude by reviewing several important database lessons learned over the previous decades that remain relevant today.
Presentation on Presto (http://prestodb.io) basics, design and Teradata's open source involvement. Presented on Sept 24th 2015 by Wojciech Biela and Łukasz Osipiuk at the #20 Warsaw Hadoop User Group meetup http://www.meetup.com/warsaw-hug/events/224872317
Michal Malohlava talks about the PySparkling Water package for Spark and Python users.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Rapid Web API development with Kotlin and KtorTrayan Iliev
Introduction to Kotlin and Ktor with flow, async and channel examples. Ktor is an async web framework with minimal ceremony that leverages the advantages of Kotlin like coroutines and extensible functional DSLs..
https://fosdem.org/2017/schedule/event/hpc_bigdata_calcite/
When working with BigData & IoT systems we often feel the need for a Common Query Language. The platform specific languages are often harder to integrate with and require longer adoption time.
To fill this gap many NoSql (Not-only-Sql) vendors are building SQL layers for their platforms. It is worth exploring the driving forces behind this trend, how it fits in your BigData stacks and how we can adopt it in our favorite tools. However building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your big data system.
Calcite has been used to empower many Big-Data platforms such as Hive, Spark, Drill Phoenix to name some.
I will walk you through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
In this one day workshop, we will introduce Spark at a high level context. Spark is fundamentally different than writing MapReduce jobs so no prior Hadoop experience is needed. You will learn how to interact with Spark on the command line and conduct rapid in-memory data analyses. We will then work on writing Spark applications to perform large cluster-based analyses including SQL-like aggregations, machine learning applications, and graph algorithms. The course will be conducted in Python using PySpark.
Apache Drill and Zeppelin: Two Promising Tools You've Never Heard OfCharles Givre
Study after study shows that data preparation and other data janitorial work consume 50-90% of most data scientists’ time. Apache Drill is a very promising tool which can help address this. Drill works with many different forms of “self describing data” and allows analysts to run ad-hoc queries in ANSI SQL against that data. Unlike HIVE or other SQL on Hadoop tools, Drill is not a wrapper for Map-Reduce and can scale to clusters of up to 10k nodes.
JEEConf 2015 - Introduction to real-time big data with Apache SparkTaras Matyashovsky
This presentation will be useful to those who would like to get acquainted with Apache Spark architecture, top features and see some of them in action, e.g. RDD transformations and actions, Spark SQL, etc. Also it covers real life use cases related to one of ours commercial projects and recall roadmap how we’ve integrated Apache Spark into it.
Was presented on JEEConf 2015 in Kyiv.
Design by Yarko Filevych: http://www.filevych.com/
Mobile device integration is hard. But not anymore. In this session you'll be able to see how you can easily use device capabilities and integrate with Beacons and Geofence. This presentation consisted in a live demo, which will be shared later on, and on a small video, to be shared as well later.
Presentation made at OutSystems NextStep Lisbon 2016.
Since the irruption in the market of the NoSQL concept, graph databases have been traditionally designed to be used with Java or C. With some honorable exceptions, there isn't an easy way to manage graph databases from Python. In this talk, I will introduce you some of the tools that you can use today in order to work with those new challenging databases, from our favorite languge, Python.
RDFa: introduction, comparison with microdata and microformats and how to use itJose Luis Lopez Pino
Presentation for the course 'XML and Web Technologies' of the IT4BI Erasmus Mundus Master's Programme. Introduction, motivation, target domain, schema, attributes, comparing RDFa with RDF, comparing RDFa with Microformats, comparing RDFa with Microdata, how to use RDFa to improve websites, how to extract metadata defined with RDFa, GRDDL and a simple exercise.
Apache conbigdata2015 christiantzolov-federated sql on hadoop and beyond- lev...Christian Tzolov
Slides from ApacheCon BigData 2015 HAWQ/GEODE talk: http://sched.co/3zut
In the space of Big Data, two powerful data processing tools compliment each other. Namely HAWQ and Geode. HAWQ is a scalable OLAP SQL-on-Hadoop system, while Geode is OLTP like, in-memory data grid and event processing system. This presentation will show different integration approaches that allow integration and data exchange between HAWQ and Geode. Presentation will walking you through the implementation of the different Integration strategies demonstrating the power of combining various OSS technologies for processing bit and fast data. Presentation will touch upon OSS technologies like HAWQ, Geode, SpringXD, Hadoop and Spring Boot.
SQL on Hadoop: Defining the New Generation of Analytics Databases DataWorks Summit
The analytics and data warehousing industries are in the midst of a major period of transformation. Since the publication of Google?s MapReduce paper, we have witnessed the appearance of Apache Hadoop, followed by the arrival of batch-oriented SQL systems like Apache Hive, and the scramble by established SQL vendors to implement Hadoop connectors. This talk addresses the recent emergence of a new generation of analytic databases inspired by Google Dremel. These databases have been designed with the goal of running real-time SQL natively on Hadoop in a manner that fully exploits the flexibility and performance of the underlying platform. Characterized by features including schema-on-read, support for semi-structured data, and pluggable storage engines, these new systems share important architectural details that distinguish them from the previous generation of analytic databases. In this talk, we will discuss the performance limitations of the connector-based approach employed by many established vendors and explain the long-term significance of Apache Hive?s data model. Then, we will unravel the novel architectural features common to next generation analytic database systems like CitusDB and Impala that make real-time SQL-on-Hadoop feasible. Finally, we will conclude by reviewing several important database lessons learned over the previous decades that remain relevant today.
Presentation on Presto (http://prestodb.io) basics, design and Teradata's open source involvement. Presented on Sept 24th 2015 by Wojciech Biela and Łukasz Osipiuk at the #20 Warsaw Hadoop User Group meetup http://www.meetup.com/warsaw-hug/events/224872317
Michal Malohlava talks about the PySparkling Water package for Spark and Python users.
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Rapid Web API development with Kotlin and KtorTrayan Iliev
Introduction to Kotlin and Ktor with flow, async and channel examples. Ktor is an async web framework with minimal ceremony that leverages the advantages of Kotlin like coroutines and extensible functional DSLs..
https://fosdem.org/2017/schedule/event/hpc_bigdata_calcite/
When working with BigData & IoT systems we often feel the need for a Common Query Language. The platform specific languages are often harder to integrate with and require longer adoption time.
To fill this gap many NoSql (Not-only-Sql) vendors are building SQL layers for their platforms. It is worth exploring the driving forces behind this trend, how it fits in your BigData stacks and how we can adopt it in our favorite tools. However building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your big data system.
Calcite has been used to empower many Big-Data platforms such as Hive, Spark, Drill Phoenix to name some.
I will walk you through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
In this one day workshop, we will introduce Spark at a high level context. Spark is fundamentally different than writing MapReduce jobs so no prior Hadoop experience is needed. You will learn how to interact with Spark on the command line and conduct rapid in-memory data analyses. We will then work on writing Spark applications to perform large cluster-based analyses including SQL-like aggregations, machine learning applications, and graph algorithms. The course will be conducted in Python using PySpark.
Apache Drill and Zeppelin: Two Promising Tools You've Never Heard OfCharles Givre
Study after study shows that data preparation and other data janitorial work consume 50-90% of most data scientists’ time. Apache Drill is a very promising tool which can help address this. Drill works with many different forms of “self describing data” and allows analysts to run ad-hoc queries in ANSI SQL against that data. Unlike HIVE or other SQL on Hadoop tools, Drill is not a wrapper for Map-Reduce and can scale to clusters of up to 10k nodes.
JEEConf 2015 - Introduction to real-time big data with Apache SparkTaras Matyashovsky
This presentation will be useful to those who would like to get acquainted with Apache Spark architecture, top features and see some of them in action, e.g. RDD transformations and actions, Spark SQL, etc. Also it covers real life use cases related to one of ours commercial projects and recall roadmap how we’ve integrated Apache Spark into it.
Was presented on JEEConf 2015 in Kyiv.
Design by Yarko Filevych: http://www.filevych.com/
Mobile device integration is hard. But not anymore. In this session you'll be able to see how you can easily use device capabilities and integrate with Beacons and Geofence. This presentation consisted in a live demo, which will be shared later on, and on a small video, to be shared as well later.
Presentation made at OutSystems NextStep Lisbon 2016.
The road to great mobile applications is complex and confusing with today's apps coming in many shapes and sizes. Choosing the right strategy from the start will turn your mobile app needs into a resounding success.
Talk performed in OutSystems NextStep 2013
Recording @https://youtu.be/EhTeao1NBls
Five fantastic tips for fabulous phone photosSmallAperture
The best camera is the one that you have with you. So how do you get the best out of your smartphone when it comes to photography? By following these five pointers! Brought to you by the editor of Photocritic and the author of Social Photography, Daniela Bowker.
‘Whizzing words’, a platform which is so indeed simple for anyone to put their thoughts, stories forward. Because we believe every story speaks for it.
http://www.whizzingwords.com
Experience either makes or breaks your app. In this session, we'll show how OutSystems 10 empowers you to create amazing applications. We're going without a safety net, so you will get to see us doing it live, in real time.
Talk performed in OutSystems NextStep Benelux 2016
Plugin smilk : données liées et traitement de la langue pour améliorer la nav...SemWebPro
Pour nourrir leur stratégie marketing et leur veille concurrentielle, les entreprises doivent surveiller le Web et donner un sens à cette grande quantité d'informations. Cette information est éparpillée et nécessite beaucoup de temps pour analyser les différentes sources et compiler les connaissances recueillies de manière intelligente. SMILK est un laboratoire commun entre l'Institut de recherche Inria et la société VISEO pour étudier le couplage fort d'algorithmes et de modèles linguistiques au niveau sémantique, l'extraction et le liage de connaissances issues des ressources du Web et la combinaison de différentes techniques de raisonnement (inférences logiques, des approximations et similitude, etc.). Dans ce contexte, nous allons présenter un prototype permettant d'enrichir les connaissances des utilisateurs naviguant sur le Web à l'aide de résultats issus du Traitement Automatique du Langage Naturel, du Web de Données et des réseaux sociaux. Notre présentation se concentrera sur la démonstration d'un plugin de navigateur facile à installer et à utiliser, qui permet d’enrichir l’expérience utilisateur avec quatre fonctions : - la démo commence par montrer comment il est possible d'identifier dans une page les entités pertinentes selon les intérêts de l'utilisateur et comment structurer les données connexes à l'aide d'une analyse linguistique dédiée ; - la deuxième partie de la démo montre comment nous lions les entités reconnues dans le texte ; - la troisième étape de la démo traite du liage d’entités pour connecter les données figurant dans le texte avec les données obtenues à partir de bases de connaissances du Web ; - enfin, dans une dernière étape la démo montre l’intégration de connaissances issues des médias sociaux pour fournir aux utilisateurs des opinions et les idées clés liées au sujet exploré. Le prototype que nous présenterons intègre entièrement les quatre fonctions précédemment définies et, dans le cadre de cette démonstration, est appliqué au domaine des cosmétiques.
Auteurs : Elena Cabrio, Jordan Calvi, Fabien Gandon, Cédric Lopez, Farhad Nooralahzadeh, Thibault Parmentier, Frédérique Segond Laboratoire Commun SMILK, Inria, VISEO
Remerciements : ces travaux de R&D et transfert sont soutenus par l’ANR au travers du laboratoire commun SMILK ANR-13-LAB2-0001-01
Arabidopsis Information Portal overview from Plant Biology Europe 2014Matthew Vaughn
An overview of the design, technical decisions, and implementation of the Arabidopsis Information Portal community-extensible data sharing and analytics platform.
API Testing. Streamline your testing process.Andrey Oleynik
Slides from IT talk: «API Testing. Streamline your testing process. A step by step tutorial»
Code on github: https://github.com/a-oleynik/soap-ui
Webinar on youtube: https://www.youtube.com/watch?v=x2ALtuCjuUo
DataArt P. https://www.meetup.com/ru-RU/DataArt-Wroclaw-IT-talk/events/246967484/?eventId=246967484 Wroclaw, 2018, February 15
Advanced Web Development in PHP - Understanding REST APIRasan Samarasinghe
ESOFT Metro Campus - Advanced Web Development in PHP - (Module VIII) Understanding REST API
(Template - Virtusa Corporate)
Resources: codeofaninja.com
Contents:
What is an API?
Comparing a website to an API
Classification of APIs
What is REST API?
What model does REST use?
REST HTTP Methods
HTTP Codes
The advantages of REST
What is CRUD?
CRUD Operations
CRUD Application Example
Simple REST API Implementation in PHP
Web root Folders and Files Structure
MySQL Database
Reading all Products
Reading one Product
Creating a Product
Updating a Product
Deleting a Product
Searching a Product
Arabidopsis Information Portal: A Community-Extensible Platform for Open DataMatthew Vaughn
Araport is an innovative model organism database resource that offers users the ability to bring their own visualizations, data sets, algorithms, and genome browser tracks and share them with their colleagues.
The Query Service is the new platform solution for querying a variety of data sources. The goal of Query Service is that administrators can configure a metadata description of the data source that can then be used by end users without detailed knowledge of the underlying data source. This session explains how to configure Query Service data sources and use them with the RESTful API or component collection.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
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.
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.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
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 .
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
4. 4
JBrowse
Data
types
Ac+ons
Chromosomes
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zoom
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Track
layering
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Data
integraDon
5. 5
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types
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InteracDon
Drill
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manipulaDon
PublicaDons
Save
results
6. 6
Science
Apps
Growing
list
of
applicaDons.
Contributed
by
community
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VisualizaDon
apps,
computaDon
apps.
Eleanor
Pence,
2014
summer
intern.
7. Arabidopsis
InformaDon
Portal
7
ThaleMine
• Instance
of
InterMine
soUware
• Classic
data
mart:
• Data
snapshot
• OpDmized
for
retrieval
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roles
within
AIP
• InteracDve
app
• Ontology
master
• Index
of
terms
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services
engine
• Web
services:
• Standard
services
• User
template
queries
JBrowse
• InteracDve
browser
app
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&
semanDc
zoom
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GFF,
BED,
BAM
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web
services
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• Chado
database
explorer
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community
annotaDon
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tools
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data
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9. Incoming
Skills
9
What is it? Read aabout it Have used it Use it a lot Could teach it
HTML/CSS 0% 0% 17% 44% 39%
Client-side Javascript 0% 17% 17% 56% 11%
JSON 0% 22% 22% 44% 11%
XML 0% 0% 28% 56% 17%
REST 11% 39% 22% 28% 0%
Oauth2 50% 50% 0% 0% 0%
Web services 0% 6% 28% 61% 6%
Git and Github 0% 0% 50% 39% 11%
Mobile-responsive design 6% 56% 33% 6% 0%
cURL 22% 28% 44% 6% 0%
Framework like Bootstrap.js 17% 44% 11% 22% 6%
Python 0% 6% 39% 39% 17%
Javascript 0% 0% 39% 44% 17%
Java 0% 6% 44% 22% 28%
Perl 0% 22% 39% 28% 11%
average
7%
20%
29%
33%
11%
Survey
taken
Sep-‐Oct
2014
in
advance
of
Araport
Developer
Workshop,
Nov
5-‐6,
at
TACC.
10. The
TIGR
Catalog
of
the
Arabidopsis
Transcriptome:
a
case
study
for
exposing
legacy
data
Presented
by
Jason
Miller,
JCVI
10
11. Web
Design
for
Dynamic
Pages
CSS
JS
Server
Browser
DB
DB
HTML
<form>
CGI
HTML
<table>
URL
HTML
<script>
WebServices
JavaScript
<table>
URL
HTML3
CSS3
HTML5
Server
Browser
TradiDonal
Requests
by
HTTP(s)
GET
or
POST.
Server-‐side
staDc
HTML
content.
Server/database
interacDon.
Content
generaDon
by
e.g.
perl
CGI.
Deliver
content-‐type=HTML
(etc.).
Modern
Requests
by
HTTP(s)
GET
or
POST.
Browser-‐side
dynamic
HTML
content.
Browser/database
interacDon.
WebServices
by
e.g.
perl
CGI.
Deliver
content-‐type=JSON
(etc.).
HTTP
HTTP
sta-c
files
ac-ve
code
11
12. Expression
Data
12
RT-‐qPCR
expression
values
for
3000
genes
of
interest
from
8
experiment
types
(single
Dssue
or
single
condiDon).
Images
of
localized
expression
for
GFP
reporter
+
promoter
construct
for
1000
genes
in
1000
ecotypes,
135K
images
in
all.
hjp://www.jcvi.org/arabidopsis/qpcr/
This
data
was
collected
at
TIGR
(now
JCVI)
by
Chris
Town
with
funding
from
the
NSF.
13. 13
The
data
offers
exciDng
possibiliDes
for
apps:
• Compare
expression
root
vs
leaf
• Compare
expression
per
treatment
• Correlate
images
to
genotypes
• Integrate
data
from
other
sources
14. Legacy
web
architecture
PHP
mySQL
HTML
form
perl
HTML
table
server
browser
14
Human-‐facing
front
end
in
HTML
form.
Srcripts
and
database
on
back
end.
Jun
Zhuang,
2009.
Hui
Quan,
2007.
15. Legacy
web
code
15
<?php
$username="access";
$password="access";
$hostName="mysql51-dmz-pro”;
if (!($connection = @ mysql_pconnect
($hostName, $username, $password)))
showerror();
?>
if ($format ne "text") {
$tmpl = HTML::Template->new
(filename => "search_return1.tmpl");
$tmpl->param
(search_table=>@result_presentation);
print header;
print $tmpl->output;
}
php
perl
16. Legacy
bugs
16
Choose
opDon
to
return
plain
text...
Returns
error
text
instead...
SoUware
error:
HTML::Template-‐
>output()
:
fatal
error
in
loop
output
:
HTML::Template
:
Ajempt
to
set
nonexistent
parameter
'elem_conc2'
-‐
this
parameter
name
doesn't
match
any
declaraDons
in
the
template
file
:
(die_on_bad_params
=>
1)
at
/usr/
local/packages/perl-‐5.16.1/lib/5.16.1/
HTML/Template.pm
line
3340.
at
/
opt/www/arabidopsis/cgi-‐bin/
arabidopsis/qpcr/SingleSearch
line
179.
For
help,
please
send
mail
to
the
webmaster
(helpdesk@jcvi.org),
giving
this
error
message
and
the
Dme
and
date
of
the
error.
17. Legacy
databases
expression
stats
reporter
images
For
each
locus
+
“Dssue”
• Absolute
expression
• RelaDve
expression
Metadata
per
image
• Line
ID
• PO
code
• Locus
ID
(free
text)
17
18. Desired
Improvements
• Break
the
monolith
– Separate
the
data
access
from
the
presentaDon
app
– Expose
the
data
with
documented
RESTful
web
services
• Enable
dynamic
interacDon
– Allow
table
interacDon
• e.g.
bujons
for
“next
page”
and
“sort
by
this
column”
– Allow
query
refinement
or
hide
&
expose
• Improve
programmaDc
accessibility
and
interoperability
– Expose
a
documented
HTTP
GET
API
taking
parameters
in
the
URL
– Provide
precise
means
to
supply
mulDple
accessions
• was
using
human-‐readable
text
formats
– Translate
anDquated
ID
formats
to
AGI
• was
mixing
TAIR
and
pre-‐TAIR
accessions,
like
“AT1G33930.1,
AT.CHR4.7.322”
– Use
precise
ontological
terms
• was
mixing
Dssue
and
condiDon
(“Leaf”
and
“NaCl”)
within
the
“Dssue”
ajribute
18
19. Araport
to
the
Rescue!
• Arabidopsis
InformaDon
Portal
(AIP)
– A
5yr
project
funded
by
NSF
(US)
and
BBSRC
(UK)
at
end
of
2013
• First
two
years:
build
a
prototype
to
prove
feasibility
• Next
three
years:
provide
producDon
quality
services
for
Arabidopsis
community
– Mission
to
build
a
sustainable
community
web
portal
• Sustainability
is
based
on
community-‐contributed
modules
• Module
=
your
data
+
your
code
+
AIP
infrastructure
• AIP
implements
data
federaDon
not
data
warehousing
• Infrastructure
that
is
light
weight,
scalable,
reproducible
• Araport.org
– Went
live
in
2014
with
2
main
apps:
ThaleMine,
JBrowse
– Now
exposing
web
services
• AIP
services
backed
by
Araport
apps
• External
services
registered,
exposed,
and
mediated
through
AIP
ADAMA
– Ready
to
provide
app
services
• app
registry
and
hosDng
for
developers
• app
store
and
workspaces
for
users
19
20. Araport
DB
Moving
RT-‐qPCR
to
Araport
Science
App
JCVI
Modify
JCVI
CGI
to...
• accept
GET,
parameters
in
the
URL
• return
JSON
Use
Araport
to...
• Install
a
Python
mediator
• Design
an
AIP-‐compliant
API
• Install
a
JavaScript
science
app
20
WebService
at
JCVI
REST
API
REST
Mediator
API
WebService
at
Araport
App
Store
21. Developer
Choices
• Wrap
legacy
system
– EnDre
system
must
remain
a
black
box
– Use
it
as
back
end
for
new
service
• An
Araport
mediator
might
convert
new
URL
to
old
HTTP
POST
• An
Araport
mediator
might
extract
new
JSON
from
old
HTML
• Re-‐engineer
the
legacy
system
– Use
an
all
new
database
(e.g.
Oracle-‐>mySQL)
or
– Use
an
all
new
server
technology
(e.g.
CGI
-‐>
EJB)
• Update
legacy
system
– Legacy
databases
are
sDll
workable
and
– Legacy
code
is
available
and
can
be
extended
21
22. Our
Choice
• Modify
the
legacy
server
– Leave
the
HTML-‐based
system
at
JCVI
– Add
a
RESTful
URL-‐to-‐JSON
web
service
at
JCVI
• Register
an
Adama
mediator
at
Araport
– Expose
a
documented,
AIP-‐compliant
web
service
– Use
the
Araport.org
base
URL
• Submit
a
science
app
to
Araport
– Use
JavaScript,
jQuery,
DataTables
22
23. Web
Service
at
JCVI
• HTML
form
– DocumentaDon
only
– Form
accepts...
• one
locus
ID
• one
condiDon
• one
output
format
– Form
submits
• HTTP
GET
• URL
exposed
parameters
• Deployed
at
JCVI
23
hjp://www.jcvi.org/arabidopsis/qpcr/
MinimalForm_ExpressionPerGenePerTissue.html
24. Web
Service
at
JCVI
• New
URL
– endpoint
replace
forms
– parameters
in
the
URL
• New
return
type:
JSON
– This
addiDon
required
a
few
lines
of
code
to
the
server
side
perl
• Support
legacy
returns:
– HMLT
– Text
as
csv
• Deployed
at
JCVI
24
hjp://www.jcvi.org/cgi-‐bin/arabidopsis/qpcr/
ExpressionPerGenePerTissue?
gene=AT1G33930.1&Dssue=Leaf&format=json
30. Web
devel
technology
stack
• HTTP,
HTML,
DOM,
JavaScript,
AJAX
• jQuery/jQueryUI/DataTables/Dojo/Moo
– programming
libraries
wrijen
in
JavaScript
• AngularJS/EmberJS/BackBone/GWT
– applicaDon
frameworks
to
help
write
big
web
apps
• Bower
– dependency
manager
• Yeoman
– scaffolding
tools
help
developers
generate
web
apps
• Grunt
– interacDve
development
environment
• Git
– version
control
and
publishing
30
34. Araport
Architecture
CLI
clients,
Scripts,
3rd
party
applicaDons
Agave
Enterprise
Service
Bus
Agave
Services
systems
apps
jobs
profile
meta
files
Physical
resources
HPC
|
Files
|
DB
Araport
API
manage
Manager
enroll
a b c d e f
AIP
&
3rd
party
data
providers
• Single-‐sign
API
Mediators
• Simple
proxy
• Mediator
• Aggregator
• Filter
on
• Throjling
• Unified
logging
• API
versioning
• AutomaDc
HTTPS
REST*
REST-‐like
SOAP
POX
Cambrian
CGI
35. AIP
Web
Services
• Backed
by
ThaleMine
(InterMine
soUware)
– Arabidopsis
genome
&
released
annotaDon
(TAIR10)
– General
purpose
API,
unauthenDcated
– User-‐configurable
AIP,
authenDcated
• Expose
your
ThaleMine
Template
Queries
• Backed
by
Tripal
(Drupal
soUware)
– Stock
center
data
– Community
annotaDon
pre-‐release
• JBrowse
tracks
– Many
already
exposed
as
Web
Services
by
EPIC
CoGo
– AIP
tracks
could
be
exposed
via
an
InterMine/JBrowse
adapter
• Backed
by
the
Community
– Provide
organizaDon,
documentaDon,
uniformity
35
36. AjribuDon
&
Provenance
• AjribuDon
mechanisms
– AjribuDon
on
science
apps
– Recursive
ajribuDon
• Provenance
mechanisms
– Provenance
of
data
displayed
– Recursive
provenance
• RecogniDon
mechanisms
– Recognize
new,
exciDng,
and
widely
used
apps
– Promote
creaDvity,
diligence,
sagacity
36
37. Further
Reading
• Portals
– I.A.I.C.
(2012)
Taking
the
Next
Step:
Building
an
Arabidopsis
Informa+on
Portal.
The
Plant
Cell.
– Lamesch
et
al.
(2012)
The
Arabidopsis
InformaDon
Resource
(TAIR):
improved
gene
annotaDon
and
new
tools.
Nucleic
Acids
Research.
– Joshi
et
al.
(2011)
MASCP
Gator:
An
AggregaDon
Portal
for
the
VisualizaDon
of
Arabidopsis
Proteomics
Data.
Plant
Physiology.
• SoUware
– Westesson
et
al.
(2012)
Visualizing
next-‐generaDon
sequencing
data
with
JBrowse.
Briefings
in
Bioinforma-cs.
– Smith
et
al.
(2012)
InterMine:
a
flexible
data
warehouse
system
for
the
integraDon
and
analysis
of
heterogeneous
biological
data.
Bioinforma-cs.
– Lee
et
al.
(2013)
Web
Apollo:
a
web-‐based
genomic
annotaDon
ediDng
pla|orm.
Genome
Biology.
– Kohl
et
al.
(2010)
Cytoscape:
SoUware
for
VisualizaDon
and
Analysis
of
Biological
Networks.
Data
Mining
in
Proteomics.
• Databases
– Eilbeck
et
al.
(2005)
The
Sequence
Ontology:
a
tool
for
the
unificaDon
of
genome
annotaDons.
Genome
Biology.
– G.O.
ConsorDum.
(2008)
The
Gene
Ontology
project
in
2008.
Nucleic
Acids
Research.
– Avraham
et
al.
(2008)
The
Plant
Ontology
Database:
a
community
resource
for
plant
structure
and
developmental
stages
controlled
vocabulary
and
annotaDons.
Nucleic
Acids
Research.
– Lyons
et
al.
(2008)
How
to
usefully
compare
homologous
plant
genes
and
chromosomes
as
DNA
sequences.
The
Plant
Journal.
[EPIC-‐CoGe]
– Brady
et
al.
(2009)
Web-‐Queryable
Large-‐Scale
Data
Sets
for
Hypothesis
GeneraDon
in
Plant
Biology.
The
Plant
Cell.
[BAR]
– Kerrien
et
al.
(2007)
IntAct—open
source
resource
for
molecular
interacDon
data.
Nucleic
Acids
Research.
37
38. Arabidopsis
InformaDon
Portal
Presenta-on
by
Jason
Miller,
JCVI
Funding
by
NSF
(USA)
BBSRC
(UK)
Contribu-ng
ins-tutes
Plant
Genomics
group
at
J.
Craig
Venter
InsDtute
Texas
Advanced
CompuDng
Center,
University
of
Texas
at
AusDn
InterMine
group
at
University
of
Cambridge
TAIR
group
at
Phoenix
Technologies
and
YOU
38