BioMake PAG 2017
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Presentation on BioMake, a GNU-Make-like utility for managing builds and complex workflows using declarative specifications. From GMOD/PAG meeting 2017
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Adapter from presentation given to NIH May 2022
https://linkml.io/linkml
Ontology Access Kit_ Workshop Intro Slides.pptx
Slides from the Ontology Access Kit (OAK) workshop, https://incatools.github.io/ontology-access-kit/
OAK is a pluralistic Python library for accessing a variety of ontologies, using either the command line or the Python library
LinkML Intro (for Monarch devs)
This document provides an overview of LinkML, a lightweight modeling language for building data schemas and knowledge graphs. It discusses how LinkML allows users to model data in a simple yet expressive way and generate outputs like JSON Schema, OWL, and RDF. LinkML aims to be developer-friendly and integrates with popular tools and standards. Several key projects currently use LinkML for tasks like building knowledge graphs and modeling genomics and clinical data.
LinkML presentation to Yosemite Group
LinkML is a modeling language for building semantic models that can be used to represent biomedical and other scientific knowledge. It allows generating various schemas and representations like OWL, JSON Schema, GraphQL from a single semantic model specification. The key advantages of LinkML include simplicity through YAML files, ability to represent models in multiple forms like JSON, RDF, and property graphs, and "stealth semantics" where semantic representations like RDF are generated behind the scenes.
Experiences in the biosciences with the open biological ontologies foundry an...
The document discusses the need for ontologies in biology to integrate data from the large number of biological databases and standards. It outlines tools for building and using ontologies, including those for end users to search and analyze data, and those for ontology engineers to develop ontologies through automated reasoning and integration. The Gene Ontology is provided as an example of an ontology that has been widely adopted for analyzing gene sets. The document advocates developing ontologies through a collaborative framework like the Open Biological and Biomedical Ontologies to promote reuse and integration across domains.
All together now: piecing together the knowledge graph of life
The document summarizes challenges in organizing biological knowledge and progress made through collaborative ontology development. It discusses how early efforts focused on individual ontologies but challenges emerged in maintenance and linking data. New approaches focus on shared principles, standardized mappings between ontologies, and modeling knowledge as graphs. Tools like Boomer and LinkML help reconcile mappings and model data, while community efforts like OBO Foundry and Biolink Model advance integration through open collaboration. Overall progress has been made but more work is needed to operationalize ontologies and build interconnected knowledge graphs.
Collaboratively Creating the Knowledge Graph of Life
The document discusses collaboratively building a knowledge graph of life by connecting existing biological ontologies. It describes how ontologies can standardize and organize biological data by representing entities and their relationships in a graph. The challenges of integrating different ontology projects are addressed through initiatives like the Open Biological and Biomedical Ontologies (OBO) Foundry. The document outlines how ontologies can be formalized using OWL and connected using tools like the Ontology Development Kit to enable discovery across domains. Current efforts like the Gene Ontology, Biolink Model, and National Microbiome Data Collaborative are leveraging these techniques to create unified, semantically queryable knowledge graphs.
Representation of kidney structures in Uberon
The document discusses representation of kidney structures in the Uberon anatomy ontology. It provides examples of kidney classes like glomerular capsule and S-shaped body represented in Uberon along with their relationships. It also discusses how Uberon integrates representations of kidney structures from other species and anatomy ontologies through equivalence axioms and cross-links.
SparqlProg (BioHackathon 2019)
SparqlProg: Logic Programs for the Biological Semantic Web. Presentation for BioHackathon, Fukuoka, Japan, 2019
Ontology Development Kit: Bio-Ontologies 2019
Presentation on Ontology Development Kit (ODK) presented 2019-07-24 at Bio-Ontologies COSI at ISMB/ECCB 2019
US2TS: Reasoning over multiple open bio-ontologies to make machines and human...
Presentation at http://us2ts.org/2019/posts/program.html in Reasoning workshop. Examples of reasoning within and across OBO ontologies
Uberon: opening up to community contributions
The document discusses Uberon, an integrative multi-species anatomy ontology. It describes Uberon's taxonomic scope covering metazoans with a focus on vertebrates. It outlines how Uberon is edited on GitHub and maintained with cross-references to other species-specific anatomy ontologies. It also discusses how phenotypes from the Phenotype and Human Phenotype Ontology are directly mapped to Uberon and species-specific anatomies, as well as considerations for which anatomy ontology a phenotype ontology should use.
Modeling exposure events and adverse outcome pathways using ontologies
This document discusses using ontologies to model exposure events, adverse outcome pathways, and phenotypes in order to support predictive toxicology. It describes existing ontologies like the Environment, Conditions, and Treatments Ontology (ECTO) and Gene Ontology Causal Activity Models (GO-CAMs) that can be used to represent exposure mechanisms and adverse outcomes. The document also presents challenges for developing an open predictive toxicology framework that leverages ontologies and linked data to make toxicology data more findable, accessible, interoperable, and reusable.
Causal reasoning using the Relation Ontology
The document discusses the need for standardized relationship types in biological data and ontologies. It provides an overview of the Relation Ontology (RO), which defines over 450 standardized relationship types organized hierarchically. RO provides a foundation for integrating multiple knowledge graphs and represents relationships in ontologies, linked data, and knowledge bases. It enables logical reasoning and inference across graphs through properties like transitivity.
US2TS presentation on Gene Ontology
This document discusses lessons learned from developing and using the Gene Ontology (GO) over the past 20 years. It covers how GO aims to systematically annotate gene function across species using an ontology. It describes how GO uses OWL constructs like subclasses, equivalence and reasoning to leverage relationships with other ontologies. It also discusses moving beyond simple annotation to represent biology accurately using causal models and graphs. Finally, it covers the Open Biology Ontology Foundry principles of collaboration, shared standards and interconnected ontologies that GO adheres to.
Introduction to the BioLink datamodel
Slides on biolink model delivered to DataCommons KC7 crosscut group. For more information see biolink.github.io/biolink-model/
Computing on Phenotypes AMP 2015
1. The document discusses using phenotypes across species to aid in interpreting genomic data from patients and improving diagnosis and treatment.
2. Building comprehensive phenotype databases from multiple sources is challenging due to disparate data on human genes/variants and model organisms.
3. The Monarch Initiative aims to link human diseases to phenotypes in model systems through an ontology-based knowledge base and portal.
4. Incorporating rich phenotypic data can improve variant filtering and interpretation by providing more context for sequencing results.
ENVO GSC 2015
The document discusses the Environment Ontology (ENVO), which aims to represent environmental entities and their relationships in a structured format. It describes the main hierarchies in ENVO, including biome, environmental feature, and environmental material. ENVO represents different levels of environmental granularity from broad biomes down to specific materials. Any material entity can act as a feature determining an environmental system. The objectives for further developing ENVO are also outlined, such as representing various environmental qualities like temperature, nutrients, and toxins.
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Scaling up semantics; lessons learned across the life sciences
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LinkML Intro July 2022.pptx PLEASE VIEW THIS ON ZENODO
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Experiences in the biosciences with the open biological ontologies foundry an...
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Explore the evolution of programming and software development and design in 2024. Discover emerging trends shaping the future of coding in our insightful analysis."
Here's an overview:Introduction: The Evolution of Programming and Software DevelopmentThe Rise of Artificial Intelligence and Machine Learning in CodingAdopting Low-Code and No-Code PlatformsQuantum Computing: Entering the Software Development MainstreamIntegration of DevOps with Machine Learning: MLOpsAdvancements in Cybersecurity PracticesThe Growth of Edge ComputingEmerging Programming Languages and FrameworksSoftware Development Ethics and AI RegulationSustainability in Software EngineeringThe Future Workforce: Remote and Distributed TeamsConclusion: Adapting to the Changing Software Development LandscapeIntroduction: The Evolution of Programming and Software Development
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Course objectives:
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2. Understanding the software design process:
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【业务选择办理准则】
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二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信bwp0011】即可
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留信网认证的作用:
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2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
【关于价格问题（保证一手价格）】
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
What’s New in Odoo 17 – A Complete Roadmap
Odoo releases a new update every year. The latest version, Odoo 17, came out in October 2023. It brought many improvements to the user interface and user experience, along with new features in modules like accounting, marketing, manufacturing, websites, and more.
The Odoo 17 update has been a hot topic among startups, mid-sized businesses, large enterprises, and Odoo developers aiming to grow their businesses. Since it is now already the first quarter of 2024, you must have a clear idea of what Odoo 17 entails and what it can offer your business if you are still not aware of it.
This blog covers the features and functionalities. Explore the entire blog and get in touch with expert Odoo ERP consultants to leverage Odoo 17 and its features for your business too.
An Overview of Odoo ERP
Odoo ERP was first released as OpenERP software in February 2005. It is a suite of business applications used for ERP, CRM, eCommerce, websites, and project management. Ten years ago, the Odoo Enterprise edition was launched to help fund the Odoo Community version.
When you compare Odoo Community and Enterprise, the Enterprise edition offers exclusive features like mobile app access, Odoo Studio customisation, Odoo hosting, and unlimited functional support.
Today, Odoo is a well-known name used by companies of all sizes across various industries, including manufacturing, retail, accounting, marketing, healthcare, IT consulting, and R&D.
The latest version, Odoo 17, has been available since October 2023. Key highlights of this update include:
Enhanced user experience with improvements to the command bar, faster backend page loading, and multiple dashboard views.
Instant report generation, credit limit alerts for sales and invoices, separate OCR settings for invoice creation, and an auto-complete feature for forms in the accounting module.
Improved image handling and global attribute changes for mailing lists in email marketing.
A default auto-signature option and a refuse-to-sign option in HR modules.
Options to divide and merge manufacturing orders, track the status of manufacturing orders, and more in the MRP module.
Dark mode in Odoo 17.
Now that the Odoo 17 announcement is official, let’s look at what’s new in Odoo 17!
What is Odoo ERP 17?
Odoo 17 is the latest version of one of the world’s leading open-source enterprise ERPs. This version has come up with significant improvements explained here in this blog. Also, this new version aims to introduce features that enhance time-saving, efficiency, and productivity for users across various organisations.
Odoo 17, released at the Odoo Experience 2023, brought notable improvements to the user interface and added new functionalities with enhancements in performance, accessibility, data analysis, and management, further expanding its reach in the market.
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BioMake PAG 2017
- 1. BioMake Ian Holmes & Christopher Mungall UC Berkeley, Berkeley Lab http://biomake.org/
- 2. Bioinformatics analysis pipelines involves chains of dependencies
- 3. GNU make CC = gcc %.o: %.c $(CC) -c -o $@ $< Rules, patterns, variables, automatic variables Compiling a C program Makefile
- 4. GNU make BWAMEM = bwa REF = ref.fasta %.sam: %.fastq $(BWA) mem $(REF) $< >$@ Aligning reads Rules, patterns, variables, automatic variables Makefile
- 5. Dependencies BWAMEM = bwa REF = ref.fasta %.sam: %.fastq $(REF).bwt $(BWA) mem $(REF) $< >$@ %.bwt: % $(BWA) index $< Timestamps, dependency graphs
- 6. Functions MAKEFILE_PATH := $(abspath $(lastword $(MAKEFILE_LIST))) MAKEFILE_DIR := $(dir $(MAKEFILE_PATH)) test1: echo $(shell ls $(MAKEFILE_DIR)) FUNC = echo $1 is $2 test2: $(call FUNC,make,cool) Special variables, functions, user-defined functions
- 7. Issues with GNU make • Only one wildcard per rule • Poor support for parallelism • Timestamps are fragile, especially on NFS • Can’t extend build logic, e.g. add qualifiers to rules Biomake fixes these!
- 8. Multiple wildcards per rule $X-$Y.sam: $X.fa.bwt $Y.fastq bwa mem $X.fa $Y.fastq >$@ biomake myref-myreads.sam
- 9. MD5 signatures $X-$Y.sam: $X.fa.bwt $Y.fastq bwa mem $X.fa $Y.fastq >$@ biomake --md5-hash myref-myreads.sam md5_hash("myref-myreads.sam",12,"0f723ae7f9bf07744445e93ac5595156"). md5_valid("myref-myreads.sam",12,"0f723ae7f9bf07744445e93ac5595156",X) :- md5_check("myref.fa.bwt",6,"b1946ac92492d2347c6235b4d2611184",X), md5_check("myreads.fastq",6,"591785b794601e212b260e25925636fd",X). .biomake/md5/myref-myreads.sam
- 10. Multiple queue engines $X-$Y.sam: $X.fa.bwt $Y.fastq bwa mem $X.fa $Y.fastq >$@ biomake -Q sge myref-myreads.sam biomake -Q slurm myref-myreads.sam biomake -Q pbs myref-myreads.sam biomake -Q poolq myref-myreads.sam
- 11. Logic extensions $X-$Y.sam: $X.fa.bwt $Y { size_file(Y,S), S < 1000000000 } bwa mem $X.fa $Y >$@ Can embed Prolog in Makefiles, or auto-translate entire Makefile to Prolog
- 12. (Some of) The Competition Language GNU- compatible? MD5? Clusters? Erlang make Erlang No No No omake OCaML Somewhat Yes No makepp Perl Yes Yes No qmake C Yes No SGE
- 13. What Biomake is not(yet) • A massively parallel data analysis framework (try Apache Spark) • A heavy-duty cloud-oriented workflow language (try Common Workflow Language) • A web application for managing jobs (try Galaxy)
- 14. What Biomake is A simple, drop-in replacement for GNU make that allows you to… • ramp up your Makefile-driven workflows to cluster scale • avoid costly rebuilds triggered by file copying & unsynchronized clocks • extend rules with wildcards and logical tests http://www.biorxiv.org/content/early/2016/12/12/093245 https://github.com/evoldoers/biomake
- 15. http://biomake.org/ • Ian Holmes • Contributors & testers • Mahesh Panchal • Markus Triska • Jan Wielemaker - creator of SWI-Prolog