Transcript Bioinformatics

Bioinformatics
Jan Taylor
A bit about me
Biochemistry and
Molecular Biology
Computer Science,
Computational Biology
Multivariate statistics
Machine learning
Experiment design
Ontology/database
development
Programming
What is bioinformatics anyway?
Definition:
Application of computational and analysis
tools to the capture and interpretation of
biological data
What does that mean?
Pattern recognition
IT/Engineering
Artificial Intelligence
Network traffic improvement
Statistics
Storage solutions
Text mining
Biological networks
GWAS
Gene expression analysis
Non-coding RNA
Protein:protein interactions
Annotation
Epidemiology
Protein folding
Surface modelling
ontologies
Sequence alignment
Homology searching
Processor development
Image processing
Simulation
Mathematics
Databases
3D structure visualisation
Personalised medicine
Comparative genomics
Evolutionary modelling
Drug design
Gene finding
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 biology
Name
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
Pharmocogeno
mics
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
CLINICAL
BIOINFORMATICS
Personalised healthcare,
Understanding of genetic,
molecular and cellular basis of disease
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