The STRING database

•Download as PPT, PDF•

0 likes•2,107 views

14th International Conference on Intelligent Systems for Molecular Biology, Software demo, Fortaleza Conference Center, Fortaleza, Brazil, August 6-10, 2006

The STRING database Lars Juhl Jensen EMBL Heidelberg

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

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]

The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time. A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. Chou-Fasman algorithm is an empirical algorithm developed for the prediction of protein secondary structure

Linkage analysis

UshaYadav24

Sequencealignmentinbioinformatics 100204112518-phpapp02

PILLAI ASWATHY VISWANATH

BioInformatics Tools -Genomics , Proteomics and metablomics

AyeshaYousaf20

Methods of Protein structure determination

EL Sayed Sabry

Functional proteomics, methods and tools

dot plot analysis

Proteomics

Yeast two hybrid

NMR of proteinJiya Ali

Mascot database

angellal2010

Computational approaches to cell cycle analysis: Current research topics (tho...

Lars Juhl Jensen

Text mining for protein and small molecule relations

Lars Juhl Jensen

What's hot

PROTEIN DATABASE

naveed ul mushtaq

The uni prot knowledgebase

Kew Sama

Ab Initio Protein Structure Prediction

Arindam Ghosh

Proteomics, definatio , general concept, signficance

KAUSHAL SAHU

Proteomics and protein-protein interaction

SenthilkumarV25

Sequence Alignment In Bioinformatics

Nikesh Narayanan

Threading modeling methods

ratanvishwas

Protein Structure DeterminationAmjad Ibrahim

Protein identication characterization

Malla Reddy College of Pharmacy

Chou fasman algorithm for protein structure prediction

Roshan Karunarathna

Linkage analysis

UshaYadav24

Sequencealignmentinbioinformatics 100204112518-phpapp02

PILLAI ASWATHY VISWANATH

BioInformatics Tools -Genomics , Proteomics and metablomics

AyeshaYousaf20

Methods of Protein structure determination

EL Sayed Sabry

Functional proteomics, methods and tools

dot plot analysis

Proteomics

Yeast two hybrid

NMR of proteinJiya Ali

Mascot database

angellal2010

What's hot (20)

PROTEIN DATABASE

The uni prot knowledgebase

Ab Initio Protein Structure Prediction

Proteomics, definatio , general concept, signficance

Proteomics and protein-protein interaction

Sequence Alignment In Bioinformatics

Threading modeling methods

Protein Structure Determination

Protein identication characterization

Chou fasman algorithm for protein structure prediction

Linkage analysis

Sequencealignmentinbioinformatics 100204112518-phpapp02

BioInformatics Tools -Genomics , Proteomics and metablomics

Methods of Protein structure determination

Functional proteomics, methods and tools

dot plot analysis

Proteomics

Yeast two hybrid

NMR of protein

Mascot database

Viewers also liked

Computational approaches to cell cycle analysis: Current research topics (tho...

Lars Juhl Jensen

Text mining for protein and small molecule relations

Lars Juhl Jensen

Literature mining: what is it, and should I care?

Lars Juhl Jensen

Systematic discovery of phosphorylation networks - Combining linear motifs an...

Lars Juhl Jensen

Room 4 Masks

viviendavies

On the margins of scholarship

Richard Davis

HW Initiative 1haloworks

Vrsovice Banner Case StudyPetr Václavek

Senso BrandingBrainventures

Kooperativa Top 10

Petr Václavek

Barbara Streisand Budapest AudioJaguit

Gil Giardelli Www Versus Wwd A Web 3

ESPMinovadoresdigitais

Holocaust Memorial TatoJaguit

Desenvolvimento Gerenciamento Produdos e serviços Aula 2008 2 mktpassos

Ivan Passos

FERRAMENTAS TECNOLÓGICAS

avz

Bcit Wayne StevensCarlos Vial

Total Aventuralisethes

Le ContaráS A Tus HijosJaguit

Não_EsperECalandula

La ProduccióNCristhi

Viewers also liked (20)

Computational approaches to cell cycle analysis: Current research topics (tho...

Text mining for protein and small molecule relations

Literature mining: what is it, and should I care?

Systematic discovery of phosphorylation networks - Combining linear motifs an...

Room 4 Masks

On the margins of scholarship

HW Initiative 1

Vrsovice Banner Case Study

Senso Branding

Kooperativa Top 10

Barbara Streisand Budapest Audio

Gil Giardelli Www Versus Wwd A Web 3

Holocaust Memorial Tato

Desenvolvimento Gerenciamento Produdos e serviços Aula 2008 2 mktpassos

FERRAMENTAS TECNOLÓGICAS

Bcit Wayne Stevens

Total Aventura

Le ContaráS A Tus Hijos

Não_Esper

La ProduccióN

Similar to The STRING database

Functional association networks - The STRING and STITCH web resources

Lars Juhl Jensen

The STRING database

Lars Juhl Jensen

Network integration of heterogeneous data

Lars Juhl Jensen

Introduction to STRING

Lars Juhl Jensen

Prediction of protein networks through data integration

Lars Juhl Jensen

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

Lars Juhl Jensen

The STRING database - Quality scores for heterogeneous interaction data

Lars Juhl Jensen

Cross-species data integration

Lars Juhl Jensen

Integration of heterogeneous data

Lars Juhl Jensen

The STRING database and related tools

Lars Juhl Jensen

Using networks to derive function

Lars Juhl Jensen

Network biology: Large-scale data and text mining

Lars Juhl Jensen

Computational approaches to cell cycle analysis: Data and databases

Lars Juhl Jensen

Data integration and functional association networks

Lars Juhl Jensen

Advanced bioinformaticsof proteomics datasets

Lars Juhl Jensen

Integration of diverse large-scale datasets

Lars Juhl Jensen

Large-scale integration of data and text

Lars Juhl Jensen

Exploring proteins, chemicals and their interactions with STRING and STITCH

biocs

STRING: Large-scale data and text mining

Lars Juhl Jensen

STRING: Prediction of protein networks through integration of diverse large-s...

Lars Juhl Jensen

Similar to The STRING database (20)

Functional association networks - The STRING and STITCH web resources

The STRING database

Network integration of heterogeneous data

Introduction to STRING

Prediction of protein networks through data integration

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

The STRING database - Quality scores for heterogeneous interaction data

Cross-species data integration

Integration of heterogeneous data

The STRING database and related tools

Using networks to derive function

Network biology: Large-scale data and text mining

Computational approaches to cell cycle analysis: Data and databases

Data integration and functional association networks

Advanced bioinformaticsof proteomics datasets

Integration of diverse large-scale datasets

Large-scale integration of data and text

Exploring proteins, chemicals and their interactions with STRING and STITCH

STRING: Large-scale data and text mining

STRING: Prediction of protein networks through integration of diverse large-s...

Recently uploaded

De-mystifying Zero to One: Design Informed Techniques for Greenfield Innovati...

Product School

FIDO Alliance Osaka Seminar: Passkeys and the Road Ahead.pdf

FIDO Alliance

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.

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/

UiPath Test Automation using UiPath Test Suite series, part 4

DianaGray10

Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap. The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies. Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques What will you get from this session? 1. Insights into SAP testing best practices 2. Heatmap utilization for testing 3. Optimization of testing processes 4. Demo Topics covered: Execution from the test manager Orchestrator execution result Defect reporting SAP heatmap example with demo Speaker: Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP

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

Elena Simperl

JMeter webinar - integration with InfluxDB and Grafana

RTTS

Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application. In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics. Length: 30 minutes Session Overview ------------------------------------------- During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana: - What out-of-the-box solutions are available for real-time monitoring JMeter tests? - What are the benefits of integrating InfluxDB and Grafana into the load testing stack? - Which features are provided by Grafana? - Demonstration of InfluxDB and Grafana using a practice web application To view the webinar recording, go to: https://www.rttsweb.com/jmeter-integration-webinar

FIDO Alliance Osaka Seminar: The WebAuthn API and Discoverable Credentials.pdf

FIDO Alliance

UiPath Test Automation using UiPath Test Suite series, part 3

DianaGray10

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

Thierry Lestable

Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...

Jeffrey Haguewood

Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows. We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases. This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams. Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.

FIDO Alliance Osaka Seminar: Overview.pdf

FIDO Alliance

Knowledge engineering: from people to machines and back

Elena Simperl

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

Product School

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.

FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf

FIDO Alliance

Leading Change strategies and insights for effective change management pdf 1.pdf

OnBoard

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.

Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf

91mobiles

From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...

Product School