Bioinformatics is an interdisciplinary research area at the interface between computer science and biological science. A variety of definitions exist in the literature and on the World Wide Web; some are more inclusive than others. Here, we adopt the definition proposed by Luscombe et al. in defining bioinformatics as a union of biology and informatics: bioinformatics involves the technology that uses computers for storage, retrieval, manipulation, and distribution of information related to biological macromolecules such as DNA, RNA, and proteins.
Track 1-1: Structural Informatics
Track 1-2: Molecular Informatics
Track 1-3: Agricultural Informatics
Track 1-4: Medical Informatics
Genomics describes the development of genome-scale technologies and their application to all areas of biological investigation. Genomics focuses on the development and application of cutting-edge methods, addressing fundamental questions with potential interest to a wide audience.
Track 2-1: Future of Genomics
Track 2-2: Cancer Genomics
Track 2-3: Genotype analysis
Track 2-4: Genome annotation
The term "proteome" refers to the entire complement of proteins, which includes the modifications made to a particular set of proteins, produced by an organism or a cellular system. It varies along with the time and dissimilar factors, such as stresses, that a cell or organism undergoes. The term "proteomics" is a large-scale comprehensive study of a specific proteome, including information on protein abundances, their variations and modifications, along with their interacting partners and networks, in order to understand cellular processes.
Track 3-1: Emerging Trends in Proteomics
Track 3-2: Protein-Protein Interactions
Track 3-3: Protein structure finding
Track 3-4: Protein structure finding
The computational biology refers to the analysis and interpretation of data. It mainly includes the following:
•Development and implementation of tools that enable efficient access to, and use and, management of various types of data
•The development of new algorithm and statistics with which to access relationship among members of large data sets, such as methods to locate a gene within a sequence, predict protein structure or function.
Track 4-1: Open software development
Track 4-2: Computational Mathematics
Track 4-3: Computational biomodeling
Track 4-4: Computational pharmacology
Track 4-5: Computational neuroscience
Biostatistics includes the study of statistics as applied to biological areas. Biological laboratory experiments, medical research, and health services research all use statistical methods. Many other biological disciplines rely on statistical methodology helps evaluate many life-and-death issues in medicine
Track 5-1: Design and analysis of clinical trials in medicine
Track 5-2: Role of biostatistics in data management
Track 5-3: Statistical genetics
Track 5-4: Descriptive Statistics
Metabolomics is a field of life science research that uses High Throughput technologies to identify and/or characterize all the small molecules or metabolites in a given cell, tissue or organism.
Track 6-1: Computer aided metabolic pathways
Track 6.2: Metabolomics
Algorithm is a step by step description of operations to be performed. The biological entities and phenomena considered in bioinformatics can be described with combinatorial and graph theoretical objects like sequences, alignments, trees, networks, etc
Track 7-1: Principle of dynamic modelling
Track 7-2: Sequence alignment
Track 7-3: Sorting Techniques
Track 7-4: Transformational grammars secondary structure prediction
Track 7-5: Graphical degree sequences
A particular active area of research in bioinformatics is the application and development of data mining techniques to solve biological problems. Analysing large biological data sets requires making sense of the data by inferring structure or generalizations from the data. Examples of this type of analysis include protein structure prediction, gene classification, cancer classification based on microarray data, clustering of gene expression data, statistical modelling of protein-protein interaction, etc.
Track 8-1: Data mining concepts and techniques
Track 8-2: Advancement in data mining tools
Track 8-3: Cluster analysis
Track 8-4: Modelling biological systems
The processes of designing a new drug by using bioinformatics tools have opened a new area of drug research and development. Computational techniques assist us in searching drug target and in designing drug in silico. Bioinformatics affects a new drug design in the following drug design path.
Track 9-1: Capabilities of translational medicine to increase success rate in pharma industry
Track 9-2: In silico drug design
Track 9-3: Advance methodologies used in drug design
The geographical scattered research centres all around the globe ranging from private to academic settings and a range of hardware and OSs are used in Bioinformatics
Track 10-1: Java in bioinformatics
Track 10-2: Use of Linux, Python, Perl, SQL in Bioinformatics
Track 10-3: Advancements in programming tools
Medical Informatics also known as Health Informatics is a field comprising information science computer science and health care, which is most popular in clinical research used for the storage of data
Track 11-1: Evidence based medicine
Track 11-2: Role of informatics in analysing rare and undiagnosed disease
Track 11-3: Population health management
Track 11-4: Translational Bioinformatics
Track 11-5: Current state of health informatics and policy initiatives
Track 11-6: Medical Informatics in Clinical research
Phylogenetic reconstruction is an attempt to discern the ancestral relationship of a set of sequences. It involves the construction of a tree, where the nodes indicate separate evolutionary paths, and the lengths of the branches give an estimate of how distantly related the sequences represented by those branches are.
Genes from different species may not have the same phylogenetic history as the species from which those sequences are taken have (although they do, obviously, have the same evolutionary history).
Track 12-1: Ancestry Prediction
Track 12-2: Molecular Phylogenetic
Track 12-3: Data visualization
The primary goal of bioinformatics is to increase the understanding of biological processes hence the applications are mainly focused on biological processes.
Track 13-1: Integrated Bioinformatics
Track 13-2: Climate change studies
Track 13-3: Forensic informatics
Track 13-4: Gene therapy
Track 13-5: Comparative studies
Track 13-6: Personalised medicine
Track 13-7: Modelling biological system
Bioinformatics is a never ending branch of biology with huge range of research opportunities
Track 14-1: Chemo informatics
Track 14-2: Role of Bioinformatics in Immunology
INAUGURATION OF BIOINFORMATICS CONFERENCE 2017
KEYNOTE SESSIONS #1
KEYNOTE SESSIONS #2
REFRESHMENTS - LUNCH BREAK
SCIENTIFIC SESSIONS - SPEECH OPPORTUNITY AVAILABLE
SCIENTIFIC SESSIONS - SPEECH OPPORTUNITY AVAILABLE
DAY #1 - CLOSURE