This database contains structured controlled vocabularies (ontologies) for various knowledge domains related to plants and their associations. It includes ontologies for plant structure, growth stages, traits, phenotypes, molecular functions, biological processes, cellular components, environments, and a taxonomy ontology. Users can search this database to find information on rice genes, proteins, QTLs, and genetic maps. Different ontologies are meant for different purposes and do not overlap.
This presentation outlines benefits for including Embase in as well designed systematic search and how you may best use Embase, based on established EBM guidelines.
This presentation outlines benefits for including Embase in as well designed systematic search and how you may best use Embase, based on established EBM guidelines.
Authors: Alice Clara Augustine, Vijayalakshmi K, Shobha Char, Naveen Sylvester, Mittur N Jagadish; Mike Edgerton
Organizations: Monsanto Research Centre, Monsanto Company
What's in a name? Better vocabularies = better bioinformatics?Keith Bradnam
Most of the pain and suffering that occurs in bioinformatics happens when database identifier 'A' in file 1, doesn't quite match database identifier 'B' in file 2...even when they are supposed to be the same identifier.
Things don't always match up for a number of reasons, most of which *should* be under our control. This talk covers a few points relating to this and briefly discusses how we should all be using curated ontologies to describe our data.
Keynote presentation from Plant and Pathogen Bioinformatics workshop at EMBL-EBI, 8-11 July 2014
Slides and teaching material are available at https://github.com/widdowquinn/Teaching-EMBL-Plant-Path-Genomics
The organism you choose was agaricus Organism ProfileAssig.docxcarlz4
The organism you choose was agaricus
Organism Profile
Assignment Instructions
:
You will write an organism profile based on literature researched about your chosen organism.
Research should come from scientific information on the internet and research articles at the APUS library. Your paper should include, but not be limited to, the following topics:
1.
Introduction/background information about the species
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Include common and scientific names of the organism, the area you and this species live (country, state, city, etc.), the area’s biome classification, etc.
2.
Life cycle of the species
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Describe the life cycle of the organism you have chosen. The life cycle of an organism refers to the series of changes in both development and growth from its beginnings as an independent life form up until maturity, when it is able to reproduce. Organisms like bacteria have relatively simple life cycles; however other organisms (e.g., plants) have very complex stages to their life cycle.
3.
Structure and Function
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Describe the structure and function of at least one major organ system of the species (e.g., digestive system, reproductive system). Choose one system and explain how this organism’s system is structured anatomically and physiologically. Identify any species-specific characteristics or adaptations that are particularly unique to this organism and explain why.
4.
Evolution of the organism
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Evolution is simply heritable change over time. Sometimes changes from one generation to the next can give individuals an advantage. Specifically a trait that increases reproductive success or survival ability could be advantageous. Include a section in your profile paper about your organism’s evolution. Here are possible ways to research the topic:
a.
Conduct a review of scientific literature to understand what is known about your organism’s past evolution. Search key words may include evolution, fossil, ancestor. Often technical reports from wildlife and
conservation agencies have
descriptions of an organism’s evolution.
b.
Summarize research on any adaptive traits. Search key words include adaptation, evolution, trait, and character.
c.
Find an article on the family tree or phylogeny of your organism. Summarize the information describing related species. Search key words might include phylogeny, phylogenetic, and genetic analysis
.
d.
Use the
Tree of Life Project
to describe the phylogeny of your organism. Start at species, if possible, and trace back to the root. In addition to your summary, include any interesting patterns or unknown data.
*
*Still have questions about how to research for the evolution section? Click
here
for a hypothetical example.
5.
Additional interests -
The diversity of biological organisms is vast. Therefore, if your organism has a particularly interesting aspect about its biology that is not covered in th.
Comparing Genomes to Determine Evolutionary RelationshipsUsing BLynellBull52
Comparing Genomes to Determine Evolutionary Relationships
Using Bioinformatics (NCBI Database)
In this activity, you will be analyzing the genomes and evolutionary relationships of a variety of species. By utilizing The NCBI (National Center for Biotechnology Information) database, you will have access to thousands of genomes. The amount of information available (as you will soon see) is absolutely astounding!! (TYPE RESPONSES IN RED or BLUE)
Directions
I. Visit the NCBI Homepage https://www.ncbi.nlm.nih.gov/ and click on “Genomes and Maps”. Next click on “Genome” (blue link in the center of the page/also found in right side bar). Next click on “Browse by Organism”.
1. What types of genomes are currently available for making comparisons?
2. How many genomes are currently available to view?
II. Next, click on “Eukaryotes” at the top. Click on a species name that looks interesting. If there is a common name for this species, it will be shown in parenthesis after the species name. Keep searching until you find a species that displays a common name and record both of the following below:
Species Name: _____________ ________________ Common Name: ____________________
III. Next, return to the “Genome” Page and click on “Genome Data Viewer”. Here you will see a phylogenetic tree that encompasses over 660 eukaryotic genomes. If you hover over the names/pictures of the organisms, it will provide the species name for each. If you click on the “+” symbols, you will be shown more detailed phylogeny(common ancestry).
3. Click on the “+” symbol to the left of Humans. Then click the single arrow symbol two more times until you see the phylogeny for all primates. Which primate has a closer common ancestor to humans, a monkey or a chimpanzee?
4. Which species has a closer common ancestor to gorillas, a monkey or a human?
5. Which species shown on the diagram has the closest common ancestor to a chimpanzee?
IV. Click on the “<<” symbol to return to the original phylogenetic tree. Hover over the “Open” circle on the very left side of the tree (common ancestor to the eukaryotes). It will indicate how many eukaryotes are classified in this phylogenetic tree. Record that number below:
Number of eukaryotes in the Phylogenetic Tree: __________
If you click and hold on this open circle, you will see that the eukaryotes are further subdivided. Continue to click and hold on the open circles displaying the GREATEST number of species (so the next one you should click & hold on is Opisthonkonta (and so on). Toward the end of the phylogeny you will see that both Whales and Pecora still have several remaining species. Click and hold on “Whales” and continue on.
6. What are the two major groups of whales displayed on the phylogenetic tree?
7. Click on a toothed or baleen whale. What is the species name? What is the common name? (You may need to hover over the blue or green circle to find the common or species name).
8. There are several genera (groups ...
A phylogenetic tree or evolutionary tree is a branching diagram or "tree" showing the inferred evolutionary relationships among various biological species or other entities—their phylogeny—based upon similarities and differences in their physical or genetic characteristics.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Ontologies gramene tutorial
1.
2.
3. Ontologies Map Ontologies Search Ontology Accession Aspect (Ontology) Synonyms Definition OntologyTerm Aspect Definition External References Derivation Annotations Ontology Term Name Object Object Accession Object Symbol Object Name Object Synonym Object Species Evidence Literature DB Genomes DB Maps DB Proteins DB Genes DB QTL DB Marker DB
5. Ontology Home Page Click here if you need more help on Ontology Click on the links of the ontologies to learn more about their use and key concepts. 2. Type term name and click search. ( option- to limit a search, click box of desired ontology type) 1. Click on “Current Ontologies” to browse terms or
6. Browsing the Ontology Database 3. Click on “BROWSE” to navigate through the desired ontology type.
7. Searching the Ontology Database Select “Gene Ontology” to search the GO database (or select one or more others appropriate to your term.) (Molecular Function is part of Gene Ontology) Type your query e.g. Example is a search for function alpha-amylase Click search
8. Gene Ontology (GO) search results Ontology Accession for the ontology term. Select to view detailed information. Exact ontology term Synonym s (if any) Definition of the ontology term
9. Ontology Term Accession Detail The lineage of alpha-amylase activity as a molecular function Term-term relationship [i]: IS A (type of) Number of database objects associated in the database with this term. Exact ontology term Definition of the term Click on link to get a complete list of set of genes/proteins/QTL/maps etc. that may be associated with the given ontology term ( see next slide for oryza sativa example.) Links to source that originally developed this ontology . External references used for defining or associated to synonyms Expandable tree. Click on term to expand.
10. Ontology Associations Links to the original entry in Gramene database. Click for TIGR gene report in Gramene. The term and its children (indirectly associated to parent term if any) for which the object type was annotated Click to download a zip file with tab delimited list of associations Method used to ascertain this association. Click on code for description. Clicking on the active column headers will sort by that column
11. Searching other ontologies Previous slides presented the gene ontology (GO) example. The same procedure must be followed if you would like to search other ontologies. The following table suggests the type of objects that are associated with different types of ontologies:
12. Other Options From Ontologyies Click to submit your ontology suggestions Learn more about Gramene ontologies Click to access download instructions Learn more about ontologies from these publications Click to learn about evidence used to make associations of ontology terms with different data types Click to download the associations Click to browse the frequently asked questions or access tutorial or help files.
13.
14. Contact Gramene Use the feedback button, located at the top of every page, to provide feedback or to ask questions about Gramene. Email Gramene at [email_address] or
Editor's Notes
Go to the Gramene Home page (http://www.gramene.org) Click the ‘Ontology’ link from the navigation bar menu on top of the page.
On the Ontology database entry page, users have the (1) browse and (2) search options to begin using the database.
To learn more about the different ontologies, go to the ‘Current Ontologies” section from the top of the page or simply scroll down after you open the ontology entry page. Follow the ‘Browse’ link to start navigating the ontology of choice.
An example using Gene Ontology (GO) to search for ‘alpha-amylase’. The search function can be used in a similar way to find plant structure, growth stages, environment, taxonomy and trait ontology terms. The query results table will give you a list of terms that matched your search. This table includes. Term accession: A stable ontology term id Aspect: suggesting a given term belongs to which type of ontology Term name: Name of the ontology term, by which it is called. Synonym: alternate names or aliases. Definition: A standardized definition of the term. See an example search for culm by selecting the ontology type &quot;plant structure(PO)&quot;. In this example you will see that &quot;culm&quot; is a synonym of &quot;stem&quot;.
In this part of the ontology browser it displays details of one TO/PO/GRO/GO terms one at a time, along with additional information on term name, term ID, synonym, definition, comments, derivation, list of parent and children terms, followed by a section on associated object types (see following section). In the &quot;derivation&quot; section the [i] or [p] or [d] symbols suggest how a given term is related to the term below (child)/above (parent) its position in the ontology tree. For more information, please see term to term relationships section. When the associations are displayed next to a term, it means that a term name was used in descibing a given object (gene/protein/QTL/mapset) either directly or sometimes indirectly to one of its children term in the tree. All the associations from a detailed level term(s) (children) are accumulated by a parent term. Therefore as we move up towards the general terms, in the derived tree, the number of associations increase. In order to find the associations (genes / qtl / proteins / mapsets) to a term of your interest, please see the number next to your term (e.g.there are #115 phenotype associations to the term stem (PO0009047). You can view the detail list of these associations by scrolling to the section of the page below the term details. The association table displays total number of objects (QTL/phenotype gene/EnsEMBL gene/proteins) and associations with &quot;term name&quot;. The number of associations could be more than the number of objects because of the greater number of evidences (citations) that were used in making the associations. Click on any one of the appropriate hyperlinked text and that will take you to a page displaying a table with a list of objects types/associations you selected. On the associations page the results table will provide information on following: Term name Object type e.g. QTL/phenotype gene/EnsEMBL gene/proteins Object accession id. (Links to the respective gene/protein/QTL/Map set for detail information) Object symbol: a gene/protein symbol/a rice gene's locus id from the genome/QTL trait symbol/Mapset short name Object name: gene/protein/QTL tait/mapset full name/ Object synonyms: any aliases or QTL published symbol Object species: species with which the objects like QTL/phenotype gene/EnsEMBL gene/proteins is associated with Evidence: Any one or more of the experimental/evidence codes that determined the association of the object to the ontology term. Every vocabulary term in the ontology has a parent and can have children of its own. As described below, these terms have a predefined set of relationship types among themselves. These relationship types are based on the biological concepts to depict the correct association to each other. Thus such an organization of vocabularies allow the users to navigate their searches using either a higher level/more generic concept. If desired they can also perform the queries using a finer level or much detailed set of terms. For example in the following image, a user can enter the search using the word &quot;root&quot; and can get a list of all the genes that are expresed in this plant part. However if one wishes to know what genes are expressed in &quot;root cortex&quot;, there is an option to browse down the tree or search using the term name to find specifically all the genes that are expressed in &quot;root cortex&quot;. Is a (instance of, type of): [i] Used to describe the relationship between a child term that represents a specific type of a more general parent term. For example in the following image: a guard cell is a type of cell; a root hair is a cell . Part of: [p] Used to indicate the relationship between a child term that is a part of the parent term. For example in the following image: the root cortex is a part of root . Develops from: [d] (used only in plant structure ontology)
All the information in the columns can be sorted as you prefer by clicking the column header/title. The association page displays 25 associations at a time. The associations can be downloaded as a zip file by clicking the &quot;Download button&quot; present at the top right corner of the association table.
In order to find the associations (genes / qtl / proteins / mapsets) to a term of your interest, please see the number next to your term (e.g.there are #115 phenotype associations to the term stem (PO0009047). You can view the detail list of these associations by scrolling to the section of the page below the term details.