The STRING database

•Download as PPT, PDF•

3 likes•782 views

The STRING database integrates known and predicted protein-protein interactions, including direct (physical) and indirect (functional) associations derived from genomic context, high-throughput experiments, co-expression and literature mining. It covers over 373 proteomes and draws on data from curated databases, textmining and computational prediction methods to provide a global network of protein interactions. STRING uses a scoring scheme to assign probabilities to interactions based on different lines of evidence and benchmarking against a gold standard reference set.

The STRING database Lars Juhl Jensen EMBL Heidelberg

Jensen et al., Drug Discovery Today: Targets, 2004

Bork et al., Current Opinion in Structural Biology, 2005

KEGG Kyoto Encyclopedia of Genes and Genomes

MIPS Munich Information center for Protein Sequences

STKE Signal Transduction Knowledge Environment

BIND Biomolecular Interaction Network Database

GRID General Repository for Interaction Datasets

von Mering et al., Nucleic Acids Research, 2005

OMIM Online Mendelian Inheritance in Man

[object Object],[object Object],[object Object],[object Object],[object Object]

Acknowledgments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

What's hot

Introduction to STRING

Lars Juhl Jensen

STRING: Large-scale data and text mining

Lars Juhl Jensen

STRING - Modeling of biological systems through cross-species data integ...

Lars Juhl Jensen

Integration of heterogeneous data

Lars Juhl Jensen

Cross-species data integration

Lars Juhl Jensen

Gene association networks - Large-scale integration of data and text

Lars Juhl Jensen

STRING - Large-scale integration of data and text

Lars Juhl Jensen

Gene association networks - Large-scale integration of data and text

Lars Juhl Jensen

Network biology: A crash course on STRING and Cytoscape

Lars Juhl Jensen

Network biology - Large-scale integration of data and text

Lars Juhl Jensen

Network biology: Large-scale data and text miningLars Juhl Jensen

Gene association networks - Large-scale integration of data and text

Lars Juhl Jensen

Large-scale integration of data and text

Lars Juhl Jensen

Biomarker bioinformatics: Network-based candidate prioritization

Lars Juhl Jensen

Systems biology: Bioinformatics on complete biological systemLars Juhl Jensen

STRING & related databases: Large-scale integration of heterogeneous data

Lars Juhl Jensen

Network biology: Large-scale data integration and text miningLars Juhl Jensen

Systems biology - Understanding biology at the systems levelLars Juhl Jensen

Cellular network biology: Proteome-wide analysis of heterogeneous data

Lars Juhl Jensen

Making gene networks through data integrationLars Juhl Jensen

What's hot (20)

Introduction to STRING

STRING: Large-scale data and text mining

STRING - Modeling of biological systems through cross-species data integ...

Integration of heterogeneous data

Cross-species data integration

Gene association networks - Large-scale integration of data and text

STRING - Large-scale integration of data and text

Gene association networks - Large-scale integration of data and text

Network biology: A crash course on STRING and Cytoscape

Network biology - Large-scale integration of data and text

Network biology: Large-scale data and text mining

Gene association networks - Large-scale integration of data and text

Large-scale integration of data and text

Biomarker bioinformatics: Network-based candidate prioritization

Systems biology: Bioinformatics on complete biological system

STRING & related databases: Large-scale integration of heterogeneous data

Network biology: Large-scale data integration and text mining

Systems biology - Understanding biology at the systems level

Cellular network biology: Proteome-wide analysis of heterogeneous data

Making gene networks through data integration

Viewers also liked

Medical data and text mining - Linking diseases, drugs, and adverse reactions

Lars Juhl Jensen

Mining heaps of data and piles of papers

Lars Juhl Jensen

Networks of proteins and diseasesLars Juhl Jensen

The Literature Text Mining Approach In Cancer Research

Lars Juhl Jensen

Integration of heterogeneous data

Lars Juhl Jensen

Network biology: Large-scale data integration and text miningLars Juhl Jensen

Identification of drug targets from side-effect similarityLars Juhl Jensen

Information integrationLars Juhl Jensen

Biological literature mining - from information retrieval to biological disco...

Lars Juhl Jensen

Biomedical literature mining

Lars Juhl Jensen

Biomedical literature mining (and why we really need open access)

Lars Juhl Jensen

Literature-based discovery: it's all about connecting dots in widely disparat...

Jack Park

Mining heterogeneous data: Understanding systems at the level of complexes an...Lars Juhl Jensen

One tagger, many uses - Illustrating the power of ontologies in named entity ...

Lars Juhl Jensen

Systems biology: Large-scale biomedical data miningLars Juhl Jensen

Bibliological data science and drug discovery

Jeremy Yang

Biomedical Relation Extraction for Knowledge Graph Completion

Claudiu Mihăilă

Viewers also liked (17)

Medical data and text mining - Linking diseases, drugs, and adverse reactions

Mining heaps of data and piles of papers

Networks of proteins and diseases

The Literature Text Mining Approach In Cancer Research

Integration of heterogeneous data

Network biology: Large-scale data integration and text mining

Identification of drug targets from side-effect similarity

Information integration

Biological literature mining - from information retrieval to biological disco...

Biomedical literature mining

Biomedical literature mining (and why we really need open access)

Literature-based discovery: it's all about connecting dots in widely disparat...

Mining heterogeneous data: Understanding systems at the level of complexes an...

One tagger, many uses - Illustrating the power of ontologies in named entity ...

Systems biology: Large-scale biomedical data mining

Bibliological data science and drug discovery

Biomedical Relation Extraction for Knowledge Graph Completion

Similar to The STRING database

Using networks to derive function

Lars Juhl Jensen

Data integration and functional association networks

Lars Juhl Jensen

Functional association networks - The STRING and STITCH web resources

Lars Juhl Jensen

Integration of diverse large-scale datasets

Lars Juhl Jensen

Data integration - Integration of functional associations using STRING

Lars Juhl Jensen

Prediction of protein networks through data integration

Lars Juhl Jensen

Advanced bioinformaticsof proteomics datasets

Lars Juhl Jensen

Systems biology: Bioinformatics on complete biological systems

Lars Juhl Jensen

Large-scale integration of data and textLars Juhl Jensen

Protein interaction networks from yeast to human

Lars Juhl Jensen

Large-scale data and text miningLars Juhl Jensen

Network integration of heterogeneous data

Lars Juhl Jensen

Networks of proteins and diseasesLars Juhl Jensen

Data and Text MiningLars Juhl Jensen

The STITCH and Reflect web resources

Lars Juhl Jensen

STRING: Protein networks from data and text mining

Lars Juhl Jensen

Protein interaction networksLars Juhl Jensen

Similar to The STRING database (17)

Using networks to derive function

Data integration and functional association networks

Functional association networks - The STRING and STITCH web resources

Integration of diverse large-scale datasets

Data integration - Integration of functional associations using STRING

Prediction of protein networks through data integration

Advanced bioinformaticsof proteomics datasets

Systems biology: Bioinformatics on complete biological systems

Large-scale integration of data and text

Protein interaction networks from yeast to human

Large-scale data and text mining

Network integration of heterogeneous data

Networks of proteins and diseases

Data and Text Mining

The STITCH and Reflect web resources

STRING: Protein networks from data and text mining

Protein interaction networks

Recently uploaded

Empowering NextGen Mobility via Large Action Model Infrastructure (LAMI): pav...

Thierry Lestable

Encryption in Microsoft 365 - ExpertsLive Netherlands 2024

Albert Hoitingh

The Art of the Pitch: WordPress Relationships and Sales

Laura Byrne

Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes? All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.

Securing your Kubernetes cluster_ a step-by-step guide to success !

KatiaHIMEUR1

Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster. However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks. In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.

Mission to Decommission: Importance of Decommissioning Products to Increase E...

Product School

Unsubscribed: Combat Subscription Fatigue With a Membership Mentality by Head...

Product School

FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf

FIDO Alliance

GraphRAG is All You need? LLM & Knowledge Graph

Guy Korland

Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs. 1. Unifying Large Language Models and Knowledge Graphs: A Roadmap. https://arxiv.org/abs/2306.08302 2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs: https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/

Neuro-symbolic is not enough, we need neuro-*semantic*

Frank van Harmelen

Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”. All of this illustrated with link prediction over knowledge graphs, but the argument is general.

LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...

DanBrown980551

Do you want to learn how to model and simulate an electrical network from scratch in under an hour? Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)! During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook. PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides: - A fully editable and extendable library for grid component modelling; - Visualization tools to display your network; - Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses; The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well. What you will learn during the webinar: - For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills; - For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf

91mobiles

FIDO Alliance Osaka Seminar: FIDO Security Aspects.pdf

FIDO Alliance

Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...

Ramesh Iyer

In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.

Transcript: Selling digital books in 2024: Insights from industry leaders - T...

BookNet Canada

The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more. Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/ Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.

GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...

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.

Monitoring Java Application Security with JDK Tools and JFR Events

Ana-Maria Mihalceanu

Accelerate your Kubernetes clusters with Varnish Caching

Thijs Feryn

Assuring Contact Center Experiences for Your Customers With ThousandEyes

ThousandEyes

When stars align: studies in data quality, knowledge graphs, and machine lear...

Elena Simperl

Bits & Pixels using AI for Good.........

Alison B. Lowndes