Network Biology: A crash course on STRING and Cytoscape

•Download as PPT, PDF•

4 likes•555 views

This document provides an overview of STRING, a protein-protein association database, and Cytoscape, a network visualization tool. It describes how STRING contains functional associations between proteins derived from genomic context, co-expression and curated databases. Cytoscape can import STRING networks and external data to map onto nodes. It offers visualization of networks through layouts and attributes, and analysis through clustering, selection filters and enrichment. The document recommends using these tools together to explore protein association networks.

Science

Lars Juhl Jensen
Network Biology
A crash course on STRING and
Cytoscape

Szklarczyk et al., Nucleic Acids Research, 2017

Korbel et al., Nature Biotechnology, 2004

Letunic & Bork, Trends in Biochemical Sciences, 2008

von Mering et al., Nucleic Acids Research, 2005

Kuhn et al., Nucleic Acids Research, 2016stitch-db.org

Binder et al., Database, 2014compartments.jensenlab.org

tissues.jensenlab.org Santos et al., PeerJ, 2015

Thank you
STRING & STITCH
Damian Szklarczyk
Nadezhda Donche
va
John
"Scooter" Morris
Helen Cook
Michael Kuhn
Stefan Wyder
Milan Simonovic
Alexander Roth
Peer Bork
Christian von Merin
g
COMPARTMENTS,
TISSUES &
DISEASES
Alberto Santos
Oana Palasca
Sune Pletscher-
Frankild
Christian Stolte
Janos Binder
Kalliopi Tsafou
Jan Gorodkin
Sean I. O’Donoghue

What's hot

STRING - Protein networks from data and text mining

Lars Juhl Jensen

Introduction to STRING

Lars Juhl Jensen

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

Lars Juhl Jensen

Network biology - Large-scale integration of data and text

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

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

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

Large-scale integration of data and textLars Juhl Jensen

Making gene networks through data integrationLars Juhl Jensen

Network biology: Large-scale data and text mining

Lars Juhl Jensen

STRING/STITCH tutorial

biocs

Gene Association Networks: Large-scale integration of data and text

Lars Juhl Jensen

Using networks to derive function

Lars Juhl Jensen

Biomarker bioinformatics: Network-based candidate prioritization

Lars Juhl Jensen

Data and Text MiningLars Juhl Jensen

Information integrationLars Juhl Jensen

Large-scale integration of data and text

Lars Juhl Jensen

Large-scale integration of data and text

Lars Juhl Jensen

What's hot (20)

STRING - Protein networks from data and text mining

Introduction to STRING

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

Network biology - Large-scale integration of data and text

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

STRING - Large-scale integration of data and text

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

Network Biology: Large-scale integration of data and text

Network biology: Large-scale data and text mining

Large-scale integration of data and text

Making gene networks through data integration

Network biology: Large-scale data and text mining

STRING/STITCH tutorial

Gene Association Networks: Large-scale integration of data and text

Using networks to derive function

Biomarker bioinformatics: Network-based candidate prioritization

Data and Text Mining

Information integration

Large-scale integration of data and text

Similar to Network Biology: A crash course on STRING and Cytoscape

Data integration with STRINGLars Juhl Jensen

Networks of proteins and diseasesLars Juhl Jensen

The STRING database and related tools

Lars Juhl Jensen

Large-scale data and text miningLars Juhl Jensen

STRING: Large-scale data and text mining

Lars Juhl Jensen

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

Protein interaction networksLars Juhl Jensen

Networks of proteins and diseasesLars Juhl Jensen

Advanced bioinformaticsof proteomics datasets

Lars Juhl Jensen

STRING & STITCH: Network integration of heterogeneous data

Lars Juhl Jensen

Turning big data and text collections into web resroucesLars Juhl Jensen

Data integration and functional association networks

Lars Juhl Jensen

Network biologyLars Juhl Jensen

Cellular network biology: Proteome-wide analysis of heterogeneous data

Lars Juhl Jensen

Unraveling cellular phosphorylation networks using computational biology

Lars Juhl Jensen

Network biologyLars Juhl Jensen

Similar to Network Biology: A crash course on STRING and Cytoscape (17)

Data integration with STRING

Networks of proteins and diseases

The STRING database and related tools

Large-scale data and text mining

STRING: Large-scale data and text mining

Network biology: Large-scale data integration and text mining

Protein interaction networks

Networks of proteins and diseases

Advanced bioinformaticsof proteomics datasets

STRING & STITCH: Network integration of heterogeneous data

Turning big data and text collections into web resrouces

Data integration and functional association networks

Network biology

Cellular network biology: Proteome-wide analysis of heterogeneous data

Unraveling cellular phosphorylation networks using computational biology

Network biology

Recently uploaded

PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION

ChetanK57

justice-and-fairness-ethics with example

azzyixes

Seminar of U.V. Spectroscopy by SAMIR PANDA

SAMIR PANDA

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Sérgio Sacani

Since volcanic activity was first discovered on Io from Voyager images in 1979, changes on Io’s surface have been monitored from both spacecraft and ground-based telescopes. Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images show that a plume deposit from a powerful eruption at Pillan Patera has covered part of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive optics at visible wavelengths.

Predicting property prices with machine learning algorithms.pdf

binhminhvu04

Hemoglobin metabolism_pathophysiology.pptx

muralinath2

Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx

muralinath2

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

Health Advances

GBSN- Microbiology (Lab 3) Gram Staining

Areesha Ahmad

In silico drugs analogue design: novobiocin analogues.pptx

AlaminAfendy1

Lateral Ventricles.pdf very easy good diagrams comprehensive

silvermistyshot

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

Areesha Ahmad

Large scale production of streptomycin.pptx

Cherry

Citrus Greening Disease and its Management

subedisuryaofficial

Structural Classification Of Protein (SCOP)

aishnasrivastava

A brief information about the SCOP protein database used in bioinformatics. The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.

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.

Richard's aventures in two entangled wonderlands

Richard 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.

general properties of oerganologametal.ppt

IqrimaNabilatulhusni

NuGOweek 2024 Ghent - programme - final version

pablovgd

Cancer cell metabolism: special Reference to Lactate Pathway

AADYARAJPANDEY1

Normal Cell Metabolism: Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function. Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released. Cell utilize energy in the form of ATP. The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process. Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP. The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos). It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation. If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use. IN CANCER CELL: Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful. Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation. This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive. Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful. Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation. This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive. introduction to WARBERG PHENOMENA: WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside. Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme. WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.

Recently uploaded (20)

PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION

justice-and-fairness-ethics with example

Seminar of U.V. Spectroscopy by SAMIR PANDA

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Predicting property prices with machine learning algorithms.pdf

Hemoglobin metabolism_pathophysiology.pptx

Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

GBSN- Microbiology (Lab 3) Gram Staining

In silico drugs analogue design: novobiocin analogues.pptx

Lateral Ventricles.pdf very easy good diagrams comprehensive

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

Large scale production of streptomycin.pptx

Citrus Greening Disease and its Management

Structural Classification Of Protein (SCOP)

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Richard's aventures in two entangled wonderlands

general properties of oerganologametal.ppt

NuGOweek 2024 Ghent - programme - final version

Cancer cell metabolism: special Reference to Lactate Pathway