Bioinformatics

Jan Taylor

A bit about meBiochemistry and Molecular Biology

Computer Science, Computational Biology

Multivariate statistics

Machine learning

Experiment design

MicrobiologyPlant ScienceEnvironment

Animal Health

Ontology/database development

Programming

Human CancerInherited Disease

What is bioinformatics anyway?

Definition:Application of computational and analysis tools to the capture and interpretation of biological data

What does that mean?

Mathematics

IT/Engineering

Statistics

Processor development

Network traffic improvement

Storage solutions

Artificial Intelligence

Pattern recognition

Text mining

Image processingSimulation

3D structure visualisation

Surface modellingontologies

Databases

Sequence alignment

Comparative genomics

Drug design

Protein:protein interactions

Gene finding

Protein folding

Homology searching

Evolutionary modelling

Gene expression analysisNon-coding RNA

GWAS

AnnotationEpidemiology

Personalised medicine

Biological networks

Challenges

• Databases and data resources– Because we need to store and retrieve lots of data

• Search and analysis tools– Because we need to infer function by comparison

• Interfaces and visualisation tools– Because we need to look at lots of data

Large scale biologyName Study of

Genomics entire genome of an organism

Transcriptomics expressed genes

Exomics coding sequences

Proteomics proteins within an organism

Metabolomics metabolites within an organism

Interactomics interactions between nucleotides, proteins and metabolites

Connectomics neural pathways in the brain

Pharmocogenomics

application of genomics to pharmacology

Phenomics observable phenotypes

Physiomics functional behaviour of an organism

Exposomics organism’s environment

Bibliomics literature concerning a topic

Genetics and genomics

• Genetics– Study of single genes, sequences, variation,

inheritance and roles in health and disease• Genomics

– Study of all the genes in an individual, their interactions with each other, the environment and roles in complex disease

Genomic data

• NGS technologies leading to massive growth of sequence data

• NHS and research labs moving to using NGS for testing

Analysis stages

• Primary– Obtaining raw data

• Secondary– Turning the raw data into genome sequence

• Tertiary– Biological interpretation

To ask biologically meaningful questions

• What genes are in chromosomal region X and are linked to disease?

• What genes cause the condition? • What is the normal function of gene Y? • What mutations have been linked to diseases A and B? • How does the mutation M alter gene function F? • What is the 3D structure of gene Y’s product?• Is gene Y expressed in condition C?• Are there any known variants of gene G?

Clinical bioinformatics

CLINICALBIOINFORMATICS

Personalised healthcare,Understanding of genetic,

molecular and cellular basis of disease

Clinical data

basic biology bioinformatics

Application of bioinformatics

• To clinical problems– Understanding disease– Treatment and management– Development of medicines– Tailoring treatment

Growth Area

• NGS becoming a diagnostic tool in genetics/genomics labs

• Emergence for the need for ‘data scientists’ – beyond genomics

• UK 100K Genome project – a driver for the NHS

Career Prospects

• Fantastic!• Clinical route:

– MSC STP training program in Clinical Bioinformatics

• Keen to recruit from mathematics and computer science backgrounds

• Research route:- Many departments now have interdisciplinary

research programs

Top Tips

• Teach yourself some biology – an understanding of the concepts and main principles of the application area

• Communication skills are vital