Nearly all living organisms share the same genetic codification (DNA) made by four chemical units. With this 4-letter language, DNA contains all the information needed for building an entire organism. Every human cell has approximately three billion letters.
Massive genomics and biomedical data generation are producing a flood of data that has given rise the field of bioinformatics.
Bioinformatics is a multidisciplinary field that involves computer science, mathematics, biomedicine and statistics.
The challenge is processing, analyzing and extracting knowledge from the huge amount of data generated by genomics research.
Use of bioinformatics
- Microbial genome – Antibiotic resistance
- Molecular / Precision/ Personalise medicine
- Gene therapy
- Drug development
- Waste/cleanup biotechnology
- Insect resistance
Relation to current technological trends
- Cloud Computing and Big Data to Provide scalable infrastructures for handling massice amounts of genomics data.
- HPC for running complex biological models.
- Artificial Intelligence and Machine Learning:
- Hidden Markow Models for DNA/RNA sequencing
- Bayesian Neuronal Networks, Deep Neuronal Networks for partner recognition and classification
- Support Vector Machines for disease/patient/case classification
- K-means and other cluster algorithms for grouping/clustering
- Fuzzy logic based algorithms for gene sequencing
- Text mining for data annotation
- Expertise in R, Phyton, Matlab, Octave, among others for genomics analysis.
- Expertise in biomedicine domain.
- Partners network in the biomedical community.
- Shifting to big data/cloud paradigm.
Development of bioinformatics tools for genomics analysis in biomedicine agriculture, aquiculture, farming, veterinary, ecology, biology.