1 / 15

Bioinformatics Jan Taylor

Bioinformatics Jan Taylor. A bit about me. Biochemistry and Molecular Biology. Microbiology. Computer Science, Computational Biology. Plant Science. Multivariate statistics. Environment. Machine learning. Animal Health. Experiment design. Ontology/database development. Human Cancer.

evadne
Download Presentation

Bioinformatics Jan Taylor

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. BioinformaticsJan Taylor

  2. A bit about me Biochemistry and Molecular Biology Microbiology Computer Science, Computational Biology Plant Science Multivariate statistics Environment Machine learning Animal Health Experiment design Ontology/database development Human Cancer Programming Inherited Disease

  3. What is bioinformatics anyway? • Definition: • Application of computational and analysis • tools to the capture and interpretation of • biological data

  4. What does that mean? Pattern recognition Biological networks GWAS IT/Engineering Gene expression analysis Artificial Intelligence Non-coding RNA Network traffic improvement Protein:protein interactions Statistics Storage solutions Annotation Epidemiology Text mining Protein folding Surface modelling Sequence alignment ontologies Homology searching Processor development Personalised medicine Simulation Image processing Comparative genomics Mathematics Databases Evolutionary modelling Gene finding 3D structure visualisation Drug design

  5. 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

  6. Large scale biology

  7. 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

  8. Genomic data • NGS technologies leading to massive growth of sequence data • NHS and research labs moving to using NGS for testing

  9. Analysis stages • Primary • Obtaining raw data • Secondary • Turning the raw data into genome sequence • Tertiary • Biological interpretation

  10. 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?

  11. Clinical bioinformatics bioinformatics basic biology Clinical data CLINICAL BIOINFORMATICS Personalised healthcare, Understanding of genetic, molecular and cellular basis of disease

  12. Application of bioinformatics • To clinical problems • Understanding disease • Treatment and management • Development of medicines • Tailoring treatment

  13. 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

  14. 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

  15. Top Tips • Teach yourself some biology – an understanding of the concepts and main principles of the application area • Communication skills are vital

More Related