Bioinformatics, computational and system biology: Future perspective for North-East India

N Irabanta Singh *

Bioinformatics derives knowledge by Computer analysis the biological and molecular biology data. It is a rapidly growing branch of biology, highly interdisciplinary, from. It uses techniques and concepts from informatics, statistics, mathematics, chemistry, biochemistry. genetics, physics, linguistics and other fields.

The biological data can be the information stored in the DNA sequences, experimental results from various sources, three dimensional protein structures, gene expression arrays, patient statistics, scientific literature, etc. An important part of research in bioinformatics is the development of methods for storage, retrieval and analysis of these data.

The concept of “information in the genetic code” has its limitations. DNA can be analysed both as a text and as a molecule that interacts with a variety of other molecules Interactions with and among proteins are governed by three dimensional structures and their dynamics and flexibility.

These in turn are obviously determined by the sequence of bases, but the behaviour of proteins cannot be fully described by reducing its analysis to a one dinensional level. The three dimensional aspects is also crucial in understanding protein sequences and protein structures.

Recent trends in bioinformatics

Bioinformatics activity was mainly related to the development of storage and organization of the growing amounts of data produced by ever more sophisticated genetic technologies, in conjunction with the infrastructural needs accompanying basic genetic research.

Bioinformatics expanded to the development and the use of computational tools for the biological interpretation of the large amounts of data. There is a very heterogeneous scientific community that covers all aspects of today’s genetic research. In the coming years the commitment to bioinformatics and system biology will be extended even further with increased funding and explicit commitment to both of these areas.

A meeting on 25 years of India’s Biotechnology Information Systems Network (BTISnet)) being initiated by the Department of Biotechnology, Government of India, New Delhi was organized at the University of Pondicherry and also conducted a symposium with the theme “25 years of Bioinformatics Past scenario and Future perspective” on 21s Feb. 2011 followed by 22" Annual meeting of Coordinators of BTISnet from 3-4 Feb., 2011. The present writer also attended the said meeting.

Key areas under rapid development include:

Comparative DNA and protein sequence analysis tools,
gene findings and genome browsers ldentification of functional non protein coding sequences, e.g. regulatory sequences
Imaging databases
Integrated sequence-based functional data from microarrays,
RNA interference
Human genetic variation data (eg single-nucleotide polymorphisms, haplotype mapsequencing)
New literature and text mining tools
New transcriptomics, metabolomics, lipidomics, glycomics, interactomics spliceomics, reactomics, etc

System biology : System biology involves developing the understanding of a biological system through mathematical and computational modeling of the interactions of components of the system leading to the expression of this understanding in qualitative and quantitative terms in particular, in terms amenable to electronics storage and communication.

Examples of biological systems” are as old as modern biology, e.g. the Krebs (1953) cycle in metabolism. However, the Krebs cycle represents an example of what arduous enzyme-by-enzyme approaches can accumulate over time. These no doubts are systems, but they are not accomplished by a systems biology approach, nor do they constitute modern systems biology.

Once this knowledge is framed in a dynamical simulation model it can, however, be used for systems biology. Systems biology approaches have long been used in physiology and in modeling the effects of medicines, as pharmacokinetics and pharmacodynamics.

The key changes that make a modern approach to systems biology necessary and possible are the very recent developments of high-through out technologies in many domains of biology as well as emerging technologies that allow the generation of new types of quantitative data at high precision and resolutions.

Further more, recent developments of complex systems theory have provided us with the mathematical concepts and tools needed to understand some of the dynamical phenomena observed in the living world. Analysis of just a small fraction of the available data has led to the realization that understanding of biology, health, disease and medicines requires an integrated approach to studying the processes involved.

Even with our current state of knowledge, systems biology has already made impressive contributions to both fundamental understanding and to direct applications to health. As an example, circadian rhythms can only be fully described with a systems biology approach.

Carefully tailored models can already make useful predictions about disease processes and how medicines can be optimally applied, constituting the beginnings of personalized medicine. For example, the time of day may be optimized for medication with chemotherapy or for diabetes treatment.

Recent trends in computational and system biology

Computational and experimental biology have for many decades been separate disciplines. System biology, on the other hand, emerged as a new discipline in which theoreticians and experimentalists closely collaborate, ideally from the planning of an experimental study.

There is a need for a continuous and iterative collaboration between modellar and experimentalist such that the modellar understands biological knowledge about the system and takes part in the definition of new experiments and the experimentalist understands the principles of converting biological information into mathematical descriptions.

The need for this close interaction partly arises from the lack of databases with sufficient information for modeling, and is in contrast to many types of bioinformatics analysis which can be based on well structured and comparatively simpler types of data such as DNA sequences.

A dominant theme is constructing complex systems from genes to cells by combining knowledge from different databases, different types of data, etc. This approach has been used with some success, but generally it creates more questions than answers. Scenarios emerging from such approaches are sensitive to the precise way the systems are built.

Data are important, but the way these data are utilized in modeling is more important. In academia, it is of a concerted approach to raise awareness about bio-informatics application and augmenting skills for its implementation in agriculture research and crop productivity improvement is underway at various institutes across India including NE region, Assam Agricultural University, Jorhat.

The Major futuristic focus is on molecular characterization of plants to come out with cures for disease pathogens, development of algorithm for gene annotation, a database on Indian IPR wheat genotypes, etc.

To develop a systematic germplasm collection for zingiberaceae of North East India, inventorization of ginger germplasm and then generate barcode data and assembly using plant specific barcode markers is currently underway at lIT, Guwahati. Significant developments have been made in germplasm collection, DNA isolation and quantification and PCR analysis.

A project is underway at IIT, Guwahati, for developing a structure prediction of the target Enzymes for causal organism of Leishmania and then doing a structural analysis and comparison of modeled enzyme structures with mammalian enzymes. At present structural modeling of the target enzymes have been done and PDB files of Glutathione Synthatese of Leishmania submitted to Protein Model database. Docking process for the said enzyme is in progress.

A Project entitled “North East Project on Tea Bioinformatics” is underway at Tea Research Association, Jorhat, Assam from August 2009 for physical mapping of Tea using BAC (Bacterial Artificial Chromosome) library and Management, Germplasm and mapping populations. Construction of a high density transcript map of Tea also included in the future plan.

Key areas under rapid development

Impressive advances have been made in modeling a number of individuals processes in physiology, e.g. in modeling the dynamics of the heart (Noble, 2007). Increasingly, however, modeling of molecular processes, involving most or all genes, gene products and metabolites is being used to understand complex disease process. However, it is vital to appreciate where models have worked, and where not.

The most successful current implementations of systems biology rely on iterative cycles of data analysis and computerized (in silico) model construction/refinement and predictions, linked to wet-laboratory (in vitro) and living specimen (in vivo) experimental design, experimentation, and data capture and storage in forms that can be represented and manipulated by computer software.

Present and future perspective of bioinformatics, computational and system biology in north east India

Since bioinformatics is central to biology education in the 21st century, its impact on the North Eastern India is also there.

Terabytes of data related to medicine and agriculture have been generated for the NE India Application of computer-based tools to be stored and distributed data will be fundamentally changing research to the young generation of NE states leading to the wide scope for the bioinformatics and its application to problems in medicine, agriculture, conservation and forensics. In light of “information revolution,’ various institutions residing at NE India have started postgraduate and research activities in the computational biology for preparing the next generation.

A bioinformatics network specially for NE regions E-journal consortium have been established under Department of Biotechnology, Government of India giving a name, NER-DeLCON (North East Region- DBT e- Library Consortium).

Conclusion

Bioinformatics, computational biology and system biology help in understanding the qualitative as well as quantitative features of the biological systems and can help in refining the existing hypothesis about biological processes. The Department of Biotechnology Government of India has a Task force entitled “Bioinformatics, Computational and System Biology” since 2009.

We must take advantage of taking fund for research in this new upcoming field. This field will be dominant perspective in future life sciences research (Academic and Applied Sciences) in North-Eastern regions of India.