Presentation is loading. Please wait.

Presentation is loading. Please wait.

COMPUTATIONAL PROCESS REPRESENTATION IN A KNOWLEDGE BASE

Published byHilja Kahma Modified over 5 years ago

Similar presentations

Presentation on theme: "COMPUTATIONAL PROCESS REPRESENTATION IN A KNOWLEDGE BASE"— Presentation transcript:

1 COMPUTATIONAL PROCESS REPRESENTATION IN A KNOWLEDGE BASE
GEORGE ACQUAAH-MENSAH, AARON GABOW, JENS EBERLEIN AND LAWRENCE HUNTER CENTER FOR COMPUTATIONAL PHARMACOLOGY THE UNIVERSITY OF COLORADO SCHOOL OF MEDICINE. DENVER, COLORADO.

2 KNOWLEDGE REPRESENTATION EXPERIMENTAL CONFIRMATION KNOWLEDGE DISCOVERY
DATA KNOWLEDGE REPRESENTATION INFERENCE RULES CONCEPT INFERENCES RELATIONSHIP DATA PROCESS SUBSTANCE STUDY CONSTRUCT ANATOMY PROTEIN LIGAND EXPERIMENTAL CONFIRMATION KNOWLEDGE DISCOVERY

3 RELATIONSHIP INPUT OUTPUT PROCESS STORAGE OUTPUT EPHEMERAL OUTPUT DISPLAY OUTPUT PHYSIOLOGICAL PROCESS BEHAVIOR NON-BIOLOGICAL PROCESS COMPUTATIONAL PROCESS DESCRIPTRON ONTOLOGY PROCESSING DATA PROCESSING PATHWAY ANALYSIS PROMOTER ANALYSIS QTL ANALYSIS LITERATURE PROCESSING

Download ppt "COMPUTATIONAL PROCESS REPRESENTATION IN A KNOWLEDGE BASE"

Similar presentations

Pat Langley Computational Learning Laboratory Center for the Study of Language and Information Stanford University, Stanford, California

Pat Langley Computational Learning Laboratory Center for the Study of Language and Information Stanford University, Stanford, California
PENN S TATE Compatible text, visual and mathematical representations for biological process ontologies Nigam Shah Penn State University.

PENN S TATE Compatible text, visual and mathematical representations for biological process ontologies Nigam Shah Penn State University.
Whiteboardmaths.com © 2004 All rights reserved 5 7 2 1.

Whiteboardmaths.com © 2004 All rights reserved
Knowledge Enabled Information and Services Science What can SW do for HCLS today? Panel at HCSL Workshop, WWW2007 Amit Sheth Kno.e.sis Center Wright State.

Knowledge Enabled Information and Services Science What can SW do for HCLS today? Panel at HCSL Workshop, WWW2007 Amit Sheth Kno.e.sis Center Wright State.
Lawrence Hunter, Ph.D. Director, Computational Bioscience Program University of Colorado School of Medicine

Lawrence Hunter, Ph.D. Director, Computational Bioscience Program University of Colorado School of Medicine
Integrating Biological and Medical Knowledge Bradley Hemminger Ph.D. School of Information and Library Science, University of North Carolina, Chapel Hill.

Integrating Biological and Medical Knowledge Bradley Hemminger Ph.D. School of Information and Library Science, University of North Carolina, Chapel Hill.
A sample processing of an input molecule. S0 S1 a a b b A1: even number of b’s Automaton A1 accepting inputs with an even number of b ’s.

A sample processing of an input molecule. S0 S1 a a b b A1: even number of b’s Automaton A1 accepting inputs with an even number of b ’s.
Machine Reasoning about Anomalous Sensor Data Matt Calder, Francesco Peri, Bob Morris Center for Coastal Environmental Sensoring Networks CESN University.

Machine Reasoning about Anomalous Sensor Data Matt Calder, Francesco Peri, Bob Morris Center for Coastal Environmental Sensoring Networks CESN University.
B IOMEDICAL T EXT M INING AND ITS A PPLICATION IN C ANCER R ESEARCH Henry Ikediego 118026.

B IOMEDICAL T EXT M INING AND ITS A PPLICATION IN C ANCER R ESEARCH Henry Ikediego
Cognitive Psychology, 2 nd Ed. Chapter 1. Defining Cognitive Psychology The study of human mental processes and their role in thinking, feeling, and behaving.

Cognitive Psychology, 2 nd Ed. Chapter 1. Defining Cognitive Psychology The study of human mental processes and their role in thinking, feeling, and behaving.
Objective 2.01 Test Review Name: Class Period:.

Objective 2.01 Test Review Name: Class Period:.
Consumer Behavior Consumer behavior research Consumer Behavior Research.

Consumer Behavior Consumer behavior research Consumer Behavior Research.
Automated Explanation of Gene-Gene Relationships Wacek Kuśnierczyk.

Automated Explanation of Gene-Gene Relationships Wacek Kuśnierczyk.
Representing, Querying and Mining Knowledge about Autism Phenotypes

Representing, Querying and Mining Knowledge about Autism Phenotypes
Chapter 4 The Building Blocks: Binary Numbers, Boolean Logic, and Gates.

Chapter 4 The Building Blocks: Binary Numbers, Boolean Logic, and Gates.
Lawrence Hunter & K. Bretonnel Cohen Center for Computational Pharmacology UCHSC School of Medicine Using.

Lawrence Hunter & K. Bretonnel Cohen Center for Computational Pharmacology UCHSC School of Medicine Using.
THEME 1: Improving the Experimentation and Discovery Process Unprecedented complexity of scientific enterprise Is science stymied by the human bottleneck?

THEME 1: Improving the Experimentation and Discovery Process Unprecedented complexity of scientific enterprise Is science stymied by the human bottleneck?
Board on Research Data and Information, National Research Council “Changing Roles of Libraries in Support of Scientific Data Activities” June 3, 2010 More.

Board on Research Data and Information, National Research Council “Changing Roles of Libraries in Support of Scientific Data Activities” June 3, 2010 More.
computer

computer
Reconstruction of Transcriptional Regulatory Networks

Reconstruction of Transcriptional Regulatory Networks

Similar presentations

Ads by Google