Developing a protein-interactions ontology Esther Ratsch European Media Laboratory.

Slides:

Advertisements

Similar presentations

Cell Communication Cells need to communicate with one another, whether they are located close to each other or far apart. Extracellular signaling molecules.

Advertisements

Signal Transduction Pathways

CELL COMMUNICATION. YOU MUST KNOW… THE 3 STAGES OF CELL COMMUNICATION: RECEPTION, TRANSDUCTION, AND RESPONSE HOW G-PROTEIN-COUPLED RECEPTORS RECEIVE CELL.

Lecture 2, Oct 11 Important points from 10/7:

SIGNALING FROM THE CELL SURFACE TO THE NUCLEUS

AP Bio: Chp.11 Cell Communication. G-protein-linked receptors: vary in their binding sites and for recognizing different G-proteins. Most have seven alpha.

2 nd lecture: Communications among cells and tissues Classification of hormones in Several Ways: According to solubility According to chemical composition.

Chapter 5 Ligand gated ion channels, intracellular receptors and phosphorylation cascades.

CHAPTER 8 Metabolic Respiration Overview of Regulation Most genes encode proteins, and most proteins are enzymes. The expression of such a gene can be.

Cell Biology Lecture 3. Function of Plasma Membrane Mechanical Support Cell Signaling Selective permeability Active transport Bulk Transport Metabolic.

CYTOKINES AND RECEPTORS Chapter 12. What Is A Cytokine? Low molecular weight proteins (30 KDa) Bind receptors, alter gene expression Can bind the secreting.

Use of Ontologies in the Life Sciences: BioPax Graciela Gonzalez, PhD (some slides adapted from presentations available at

Signal Transduction Pathways

Signaling and the Signal Transduction Cascade. Question?????? External Stimulus Inside cell Nucleus, Gene transcription Other cellular effects.

Internet tools for genomic analysis: part 2

AP content - SBI4UP Mrs. Franklin.  The trillions of cells within an organism must communicate with one another to coordinate chemical reactions and.

IGF in circulation The majority (> 75 %) exists as bound form –IGF binding proteins (IGFBPs) IGFBPs –6 proteins and several related proteins –Serum IGFBP.

Signal Transduction II Transduction Proteins & Second Messengers.

Cell signaling Cells do not work in isolation but continually ‘talk’ to each other by sending and receiving chemical signals to each other. This process.

BTN323: INTRODUCTION TO BIOLOGICAL DATABASES Day2: Specialized Databases Lecturer: Junaid Gamieldien, PhD

Cell signaling Lecture 8. Transforming growth factor (TGF β) Receptors/Smad pathway BMP7 TGF β1, TGF β2, TGF β3 Dpp Inhibins Activins TGF β receptors.

Books Molecular Cell Biology Lodish

B. Signal Transduction Pathway (cell signaling)

Synthetic biology: New engineering rules for emerging discipline Andrianantoandro E; Basu S; Karig D K; Weiss R. Molecular Systems Biology 2006.

 Binding sites for several key transcription factors, including nuclear factor (NF)-kB and various interferon regulatory factor (IRF) proteins, are present.

SPH 247 Statistical Analysis of Laboratory Data 1May 14, 2013SPH 247 Statistical Analysis of Laboratory Data.

Chapter 11: Cell Communication. Essential Knowledge 2.e.2 – Timing and coordination of physiological events are regulated by multiple mechanisms (11.1).

Unit 1 Cell and Molecular Biology Section 7 Signalling.

Cytokines, Growth Factors and Hormones SIGMA-ALDRICH.

Cell Signaling Ontology Takako Takai-Igarashi and Toshihisa Takagi Human Genome Center, Institute of Medical Science, University of Tokyo.

You have worked for 2 years to isolate a gene involved in axon guidance. You sequence the cDNA clone that contains axon guidance activity. What do you.

Passive vs. active transport Passive transport is simply transport down an electrochemical gradient until equilibrium is reached Active transport results.

Cell Signaling basics.

Biomembrane and Cell signalling BCH 452(V) Cell To Cell Comunication Dr. Samina Hyder Haq Assistant professor Dept of biochemistry Collage of Science King.

Predicting protein degradation rates Karen Page. The central dogma DNA RNA protein Transcription Translation The expression of genetic information stored.

 Regulation of Cell Number and Cancer Cells Special Limited Edition Packet Tuesday, November 10,

1 Gene function annotation. 2 Outline  Functional annotation  Controlled vocabularies  Functional annotation at TAIR  Resources and tools at TAIR.

Cell Communication.

NY Times Molecular Sciences Institute Started in 1996 by Dr. Syndey Brenner (2002 Nobel Prize winner). Opened in Berkeley in Roger Brent,

Control of the Cell Cycle, Cell Signaling and Cancer Chapter 10 Section 9.3 & Chapter 5 Section 5.6 Biology In Focus AP Biology 2014 Ms. Eggers.

Cell Communication Chapter 11.  Trillions of cells in multicellular organisms must communicate with each other to coordinate their activities.  In unicellular.

Cell Communication Chapter Cell Communication: An Overview  Cells communicate with one another through Direct channels of communication Specific.

Extracellular signal molecule

Cell Communication Chapter 11.

Introduction to biological molecular networks

Cell Communication (Chpt. 11) Chapter 11. Overview of Cell Signaling Signaling evolved early in history of life Communicating cells may be close together.

JAK-STAT Signaling Pathway.

Chapter 15- Cell Communication Part I- General signaling strategies

The Membrane Plays a Key Role in a Cell’s Response to Environmental Signals Cells can respond to many signals if they have a specific receptor.

You Must Know  3 stages of cell communication Reception, transduction, & response  How G-protein-coupled receptors receive cell signals & start transduction.

Chemical messengers. intro Chemical messengers include neurotransmitters (very short distance), paracrine agents (short distance) and hormones (long distance)

Please turn in the Unknown Solutions Lab Remember: We will vote on T-shirt designs on Monday.

Signal Transduction AP Biology Unit 3 Cell to Cell Communication Can occur in both eukaryotes and prokaryotes How? –Mostly through chemical signals –Can.

Transduction of Extracellular Signals Specific receptors in plasma membranes respond to external chemicals (ligands) that cannot cross the membrane: hormones,

Chapter 11 RQ 1. What is a type of “local signaling” for cells? 2. What is communicated through “long distance” signaling? 3. What is the first stage.

Interferons Induction of synthesis Induction of antiviral activity Antiviral activities induced by interferons  and  Antiviral activities induced by.

BCB 570 Spring Signal Transduction Julie Dickerson Electrical and Computer Engineering.

Signal transduction The process of converting extracellular signals into cellular responses. extracellular signaling molecules (ligands) synthesized and.

Protein Receptors & Signal Transduction

Lecture 16 Signal Transduction Chapter 13.

INTRODUCTION TO ENDOCRINOLOGY I

Immune Receptors and Signal Transduction

Developing a protein-interactions ontology

Chap. 16 Problem 1 Cytokine receptors and RTKs both form functional dimers on binding of ligand. Ligand binding activates cytosolic kinase domains which.

Cell Signaling.

Volume 52, Issue 3, Pages (March 2010)

Cell Communication (1.4) – Part 1

Growth Hormone Receptor

Volume 7, Issue 1, Pages 1-11 (July 1997)

Overview of molecular JAK signaling.

Presentation transcript:

Developing a protein-interactions ontology Esther Ratsch European Media Laboratory

PIOG Protein Interactions Ontology Group Computer scientists: –Philipp Cimiano Lavin (IMS Stuttgart, EML Heidelberg) –Isabel Rojas (EML Heidelberg) Computational linguists: –Uwe Reyle (IMS Stuttgart) –Jasmin Saric (EML Heidelberg) Biologists: –Esther Ratsch (EML Heidelberg) –Jörg Schultz (MPI for Molecular Genetics Berlin) –Ulrike Wittig (EML Heidelberg)

Motivation Why protein interactions? –protein function analysis –larger datasets Why an ontology? –clear domain model –storage and understanding of data –information retrieval from text –retrieve hidden information, inferencing

What is a signal transduction pathway? signal from outside is transduced to the nucleus often phosphorylation cascade signal change transcription

Why are they important? control of cellular processes communication between cells response to environmental changes regulatory network stable system, single mutations may be overriden by other pathway complex network enables complex behaviour

Jak-Stat pathway ligand cytokine receptors JAKs P P P STAT monomers P P PP PP nucleus target genes P P P tyrosine residues P P

General approach Identify scope of the ontology Identify concepts involved and their properties How to represent them? Define rules and constraints Formalisation Scope Concepts Representation Rules/Constraints Formalisation

The scope Ontology that represents interactions between proteins and other cellular compounds Restriction on molecular detail: amino acids Concentration on signal transduction pathways in initial phase no quantitative properties are modeled Scope Concepts Representation Rules/Constraints Formalisation

Identify concepts: Interacting compounds Different kinds of compounds: proteins, genes/DNA, ions,... Composition of compounds, e.g. amino acids, domains DNA region Jak Stat TAD LZ DBD SH3SH2 Y Domain organisation of Stat proteins Scope Concepts Representation Rules/Constraints Formalisation

Properties of compounds Characteristics: molecular weight, sequence, isoelectric point... Interaction potential: modifications, location, binding partners Scope Concepts Representation Rules/Constraints Formalisation nucleus P P X

Identify concepts: Interactions I –Control/Regulation –Biochemical Interactions –Logical Interactions –Bind/Dissociate –Formation –Integrity –Availability –Change of Location –Modification of Structure –Special Processes/ Reactions –Order Different types of interactions: phosphorylation, binding, translocation... Other classification: grouping of > 100 verbs (Swissprot)  11 not disjoint classes Scope Concepts Representation Rules/Constraints Formalisation

Representation of proteins General characteristics: sequence, molecular weight,... Protein state: –location –list of modifications –list of binding partners StatState3(cytoplasm, phosphorylatedAtResidue701, Stat) P P JakState1(cytoplasm, none, cytokine-receptor) Scope Concepts Representation Rules/Constraints Formalisation

Representation of interactions Event with pre- and postconditions not pevent ep t phosphorylation P not phosphorylatedphosphorylated Scope Concepts Representation Rules/Constraints Formalisation

Rules and constraints Simple hierarchies: nucleolus inside nucleus, Stat1 is a Stat is a protein Rules for the definition of interactions Consistency checking Knowledge retrieval Scope Concepts Representation Rules/Constraints Formalisation

Rules and constraints: example „Protein A is phosphorylated by B at position X.“  A and B are located in the same compartment  A was not modified at X before  A is phosphorylated at X afterwards  B is a protein kinase, which is a protein  dependent on X, B is either a S/T-kinase or a Y-kinase Scope Concepts Representation Rules/Constraints Formalisation

Phosphorylation of a protein by a kinase at a distinct residue S/T-kinase phosphorylation Formalisation: phosphorylation Scope Concepts Representation Rules/Constraints Formalisation

Challenges met Multidisciplinarity of the group –Different vocabularies  clear expression, fewer ambiguities –Different goals, different needs  not restricted to one goal –Different experiences  mutual benefit Domain

Complexity of the domain Granularity of information –detail of compound part protein: Stat domain: SH2-domain amino acid: tyrosine701 –detail of protein identity protein family: Jak, Stat protein type: Jak2, Stat5 organism specific protein: Jak2_human, Jak2_rat

Complexity of the domain II description detail: –not known: no data available –doesn‘t have: no binding partners –don‘t care: not important for a certain interaction

What comes next? Go on with development of ontology Projects using the ontology: –integration in larger ontology on metabolic pathways –application to TIGERSearch (see poster)

Acknowledgements Protein Interactions Ontology Group Computer scientists: –Philipp Cimiano Lavin (IMS Stuttgart, EML Heidelberg) –Isabel Rojas (EML Heidelberg) Computational linguists: –Uwe Reyle (IMS Stuttgart) –Jasmin Saric (EML Heidelberg) Biologists: –Esther Ratsch (EML Heidelberg) –Jörg Schultz (MPI for Molecular Genetics Berlin) –Ulrike Wittig (EML Heidelberg)