Knowledge Discovery from Biological and Clinical Data:

BASIC BACKGROUND

Jonathan’s rules : Blue or CircleJessica’s rules : All the rest

What is Datamining?

Whose block is this?

Jonathan’s blocks

Jessica’s blocks

What is Datamining?

Question: Can you explain how?

Knowledge Discovery from Biological and Clinical Data:

MOTIVATION

• Complete genomes are now available

• Knowing the genes is not enough to understand how biology functions

• Proteins, not genes, are responsible for many cellular activities

• Proteins function by interacting with other proteins and biomolecules

GENOME PROTEOME

INTERACTOME

Driving Forces: Genes, Proteins, Interactions, Diagnosis, & Cures

If we figure out how these work, we get these Benefits

To the patient:Better drug, better treatment

To the pharma:Save time, save cost, make more $

To the scientist:Better science

To figure these out,we bet on...

“solution” = Data Mgmt + Knowledge Discovery

Data Mgmt =Integration + Transformation + Cleansing

Knowledge Discovery = Statistics + Algorithms + Databases

Knowledge Discovery from Biological and Clinical Data:

ACCOMPLISHMENT

Predict Epitopes,Find Vaccine Targets

• Vaccines are often the only solution for viral diseases

• Finding & developing effective vaccine targets (epitopes) is slow and expensive process

• Develop systems to recognize protein peptides that bind MHC molecules• Develop systems to recognize hot spots in viral antigens

Recognize Functional Sites,Help Scientists

• Effective recognition of initiation, control, and termination of biological processes is crucial to speeding up and focusing scientific experiments

• Data mining of bio seqs to find rules for recognizing & understanding functional sites

Dragon’s 10x reduction of TSS recognitionfalse positives

Diagnose Leukaemia, Benefit Children

• Childhood leukaemia is a heterogeneous disease

• Treatment is based on subtype

• 3 different tests and 4 different experts are needed for diagnosis

Curable in USA, fatal in Indonesia

• A single platform diagnosis based on gene expression• Data mining to discover rules that are easy for doctors to understand

Understand Proteins,Fight Diseases

• Understanding function and role of protein needs organised info on interaction pathways

• Such info are often reported in scientific paper but are seldom found in structured databases

• Knowledge extraction system to process free text • extract protein names• extract interactions

Knowledge Discovery from Biological and Clinical Data:

OPPORTUNITY

• Objectives– Translate inspiration

from biological systems into advancement of life and computing sciences

– Advance data mining technologies in decision systems for complex problems

Direction & Plan

• To work on practical systems for– data mining

– data cleansing

– knowledge extraction

• Applied to – gene regulation

– protein interaction

– clinical data analysis

– ligand-receptor interaction

a b

It seems that configurationa is less likely than b. Canwe exploit this?

E.g., How to Get More Out of the Same Experiments?

• How to recognize false positives from two-hybrid and other types of high-throughput protein interaction experiments?

• Some initial thoughts:

E.g., How to Improve Classifier Algorithms?

• SVM, ANN, etc.

– Good accuracy,

– but not easy to understand

• C4.5, CART, etc.

– Clear rules,

– but lower accuracy

• Why can’t we have a classifier algorithm that

– handles high dimension

– achieves high accuracy

– provides understandable rules

Who will you be working with...

Limsoon Wong

See-Kiong Ng

Jinyan Li

Vladimir Bajic

Vladimir Brusic

I2R

SOC

Mong Li Lee

Ken Sung

Wynne Hsu