using relational structure for learning and modeling in biomedical and social domains
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Using Relational Structure for Learning and Modeling in Biomedical and Social Domains. Mark Goadrich Computer Science and Mathematics Centenary College of Louisiana Natural Science Colloquium November 6th, 2007. Overview. First-Order Logic and Machine Learning The world is full of Objects - PowerPoint PPT PresentationTRANSCRIPT
Using Relational Structure for Learning and Modeling in Biomedical and Social
DomainsMark Goadrich
Computer Science and Mathematics
Centenary College of Louisiana
Natural Science ColloquiumNovember 6th, 2007
Overview• First-Order Logic and Machine Learning
– The world is full of Objects– Model these Objects to understand the
world
• Inductive Logic Programming– Objects and Relations/Properties
• Agent-Based Modeling– Objects and Interactions/Behaviors
Bongard Problems
• 6 positive examples of a concept on left• 6 negative examples on right• How to learn this concept using a computer?
First-Order Logic using PROLOG
• Objects– e3, t1, t2, c1
• Types– example(e3)– triangle(t1)– triangle(t2)– circle(c1)Positive Example 3
• Relations– has_shape(e3, t1)– has_shape(e3, t2)– has_shape(e3, c1)– inside(t2, c1)– left(t2, t1)– size(c1, 2.5)– above(t2, t1) …
Repeat this process for each example in dataset
Inductive Logic Programming (ILP)
• Search the space of possible rules “positive(E) :- …”
• Judge rule quality by positive - negative coverage positive(E) positive(E):- has_shape(E, A)
positive(E):- has_shape(E, A), triangle(A)
positive(E) :- has_shape(E, A), has_shape(E, B), triangle(A), circle(B), inside(A, B).
Research Issues in ILP
• Enormous space to search for rules• Enormous number of examples• Incorporation of continuous features• Learning of probabilistic rules• Evaluation of rule quality
• Survey of ILP domains and future interests
Mutagenesis
• Designing effective and selective drugs
• Represent chemicals as atoms and bonds between them
atm(127, 127_1, c, 22, 0.191 )bond(127, 127_1, 127_6, 7 )
• Learned mutagenic rule:
mutagenic(A) :- atm(A, B, c, 27, C), bond(A, D, E, 1), bond(A, B, E, 7).
Breast Cancer
Detection• Large dataset of abnormalities
found in mammograms
• Not enough radiologists
• Relational features– More than one abnormality
per mammogram– More than one mammogram
per person over time
malignant(A) :- not asymmetric(A), in_same_mammorgram(A, A2), spiculated_margin(A2), not distorted(A2)
Robot Scientist• Represent Metabolic
Pathways as a Regulatory Network Graph
• Knock out genes, and then systematically deduce the unknown function
• Try to learn the network from time-series microarray data
Social Networks
• People are connected by friendships into networks
• Each person has likes/dislikes, possibly influenced by their network
• Can we learn your interests based on who you know and what they like? Targeted advertisements?
Netflix Prize• What movies should Netflix
recommend you watch next?
• Large relational dataset– Movies– Titles– Ratings– Friends– Friend’s ratings– Genre
• $1 million if you achieve 10% improvement over their algorithm Cinematch
Zendo• Board game about inductive
logic
• Master creates a rule which some 3-D pyramid structures fit and others do not
• Players build structures and try to guess the Master rule
• Easier to design computer Master to decide if a structure fits the rule
• Harder to design computer Player that must efficiently guess the rule
Crab Claws
• What physical characteristics distinguish between two species?
• Within the same species, what changes due to growth, diet and their relation to predation?
• Find the “shock graph” of each image
• Use ILP to learn differences based on these graphs
Agent-Based Modeling• Objects have interactions with each other
– Flocks of Birds, Schools of Fish• Separation• Alignment• Cohesion
• Objects interact with their environment– Ant Foraging, Pheromones, Traffic Laws
• Agent-Based Modeling (ABM)– Create discrete-time computational simulation– Align models with known behavior– Vary parameters to test new hypotheses
Cellular Process
Social Science
Conclusions• First-Order Logic combines with ILP and
ABM to create a powerful representation of the world
• Research Opportunities– Social Networks– Zendo Player– Claws and Shock Graphs– Cellular Simulation– Social Simulation – [Insert your favorite dataset here]