Track Categories

The track category is the heading under which your abstract will be reviewed and later published in the conference printed matters if accepted. During the submission process, you will be asked to select one track category for your abstract.

Drug discovery is a lengthy and highly expensive process that uses a variety of tools from diverse fields. To facilitate the process, several biotechnologies, including genomics, proteomics, cellular and organismic methodologies have been developed. The present review aims to provide a basic understanding of proteomics research by discussing the methods used to study large numbers of proteins and by reviewing the application of proteomics methods to identify biomarkers, to identify drug target and to conduct drug’s mode of action and toxicology studies. It is expected that this will lead to important new insights into disease mechanisms and improved drug discovery strategies to produce novel therapeutics.

  • Track 1-1Goal of biomarker discovery
  • Track 1-2 Identification and assignment of candidate target
  • Track 1-3Recombinant protein microarray
  • Track 1-4Computational drug design
  • Track 1-5Drug toxicity
  • Track 1-6Chemical proteomics
  • Track 1-7Pharmacoproteomics.

Protein expression refers to the way in which proteins are synthesized, modified and regulated in living organisms. In protein research, the term can apply to either the object of study or the laboratory techniques required to manufacture proteins. Protein analysis is the bioinformatics study of protein structure, protein interaction and function using database searches, sequence comparisons, structural and functional predictions.

  • Track 2-1Protein expression
  • Track 2-2Gel-free & based proteomics techniques
  • Track 2-3Functional proteomics
  • Track 2-4Protein biochemistry
  • Track 2-5Protein interaction
  • Track 2-6Protein identification
  • Track 2-7Protein profiling
  • Track 2-8Protein characterization
  • Track 2-9Protein analysis
  • Track 2-10Recombinant proteins

More than a thousand proteins are thought to contribute to mammalian chromatin and its regulation, but our understanding of the genomic occupancy and function of most of these proteins is limited. We have used a chromatin proteomic profiling approach to produce a catalogue of proteins associated with genomic regions whose chromatin is marked by specific modified histones. A substantial number of the newly identified proteins are associated with human disease. Future chromatin proteomic profiling studies should prove valuable for identifying additional chromatin-associated proteins in a broad spectrum of cell types.

  • Track 3-1Chromatin regulators enriched in chip-ms
  • Track 3-2Transcription factors and cofactors enriched in chip-ms
  • Track 3-3Cell culture
  • Track 3-4Antibodies
  • Track 3-5Chip-ms and chip-seq

Protein microarrays, also known as protein chips that provides a versatile platform for characterization of hundreds of thousands of proteins in a highly parallel and high-throughput way. It is an important class of proteomic technologies that  are in fast becoming crucial tools in biochemistry and molecular biology. Two major classes of protein microarrays are defined to describe their applications: analytical and functional protein microarrays. Analytical protein microarrays, mostly antibody microarrays, have become one of the most powerful multiplexed detection technologies. Functional protein microarrays are being increasingly applied to many areas of biological discovery, including studies of protein interaction, biochemical activity, and immune responses.

  • Track 4-1Analytical protein microarrays
  • Track 4-2Functional protein microarrays
  • Track 4-3Protein-protein interactions
  • Track 4-4Protein-dna interactions
  • Track 4-5Protein-drug Interactions
  • Track 4-6Identification of kinase substrates on protein chips
  • Track 4-7Profiling immune responses
  • Track 4-8Detection of antigen-antibody interaction using protein microarrays

Proteomics technologies are used for early detection and diagnosis of cancers for the development of novel therapeutic agents. Identification of biomarker and also the study of protein expression of the cancer are studied through proteomics platforms. These studies have led to the development of discovering new drugs and targeted therapeutics towards the tumour cells. Detection, prognosis, diagnosis and therapy of breast cancer is now possible with the advancements in the field of proteomics along with the use of mass spectrometry. The discovery of the protein patterns has enabled researchers to distinguish the disease and disease free-state associated with breast cancer has been uncovered with the development of proteomics technologies. This discovery leads to personalized therapy for the patients. Proteins expressed or found in the serum, plasma and the tumour cells using the novel methodologies provide a better view of the heterogeneity of the cancers.

  • Track 5-1Protein expression of cancer genes
  • Track 5-2Genetic alteration
  • Track 5-3Somatic mutations
  • Track 5-4Translocations
  • Track 5-5Missense mutations
  • Track 5-6Frameshift mutations
  • Track 5-7Germline mutations
  • Track 5-8Nonsense mutations
  • Track 5-9Splicing mutations
  • Track 5-10Tumour biology

Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. As an interdisciplinary field of science, bioinformatics combines computer science, statistics, mathematics, and engineering to analyse and interpret biological data.  

  • Track 6-1Evolutionary bioinformatics
  • Track 6-2Structural bioinformatics
  • Track 6-3Next generation sequencing
  • Track 6-4Web services in bioinformatics
  • Track 6-5Programming languages in bioinformatics
  • Track 6-6High performance computing in bioinformatics
  • Track 6-7Algorithm biology & health informatics
  • Track 6-8Applied bioinformatics and public health microbiology

Neuroproteomics   is the study of the protein complexes and species that make up the nervous system. These proteins interact to make the neurons connect in such a way to create the complication, that nervous system is known for. Neuroproteomics is a complex field that has a long way to go in terms of profiling the entire neuronal proteome. It is a relatively recent field that has many applications in therapy and science. So far, only small subsets of the neuronal proteome have been mapped, and then only when applied to the proteins involved in the synapse. Neuroproteomics   is a step in the right direction of identifying bio-markers that can be used to detect diseases.

  • Track 7-1Protein separation
  • Track 7-2Protein identification
  • Track 7-3Drug addiction
  • Track 7-4Brain injury
  • Track 7-5Nerve growth
  • Track 7-6Cellular neuroscience
  • Track 7-7Molecular neuroscience

Most cells in the human body are subject to continuous change. Old or dysfunctional cells are replaced on a regular basis. In addition, each cell is constantly sensing its environment, and can adapt in response to specific cues, if necessary. This is essential to ascertain proper physiological function. All signal transduction processes consist of individual protein-protein interactions, which are assembled into pathways and networks. They are regulated by protein abundance and localization, and modulated by post-translational modifications. Any drug intervention, therefore must alter at least of these features in order for it to be effective.

  • Track 8-1Cell signalling in multicellular organisms
  • Track 8-2Receptors for cell motility and differentiation
  • Track 8-3Signalling pathways
  • Track 8-4Intraspecies and interspecies signalling
  • Track 8-5Paracrine signalling
  • Track 8-6Synaptic signalling
  • Track 8-7Autocrine signalling
  • Track 8-8Endocrine signalling
  • Track 8-9Signalling through cell-cell contact

Metabolomics is a term that describes the measurement and analysis of metabolites, such as sugars and fats, in the cells of organisms at specific times and under specific conditions. Metabolomics allows researchers to measure physiological effects and to monitor for adverse reactions to drugs. Metabolomics  is of interest to physicians because it may lead to improvements in the diagnosis and treatments of human diseases.

  • Track 9-1Metabolic fingerprinting
  • Track 9-2Metabolic profiling
  • Track 9-3Metabolic targeting
  • Track 9-4Environmental metabolomics
  • Track 9-5Metabonomics
  • Track 9-6Exometabolomics
  • Track 9-7Metabolites
  • Track 9-8Molecular medicine
  • Track 9-9Molecular pathology

Transcriptome sequencing covers a wide variety of simple mRNA profiling to discovery and analysis of the entire Transcriptome. These, collectively called RNA-Sequence, are extremely popular for next generation sequencing platforms. Since it is a sequencing based techniques, it is well suited for RNA editing and allele specific expression.

  • Track 10-1Mrna-seq
  • Track 10-2Small rna-seq
  • Track 10-3Whole transcriptome sequencing
  • Track 10-4Mapping gene and exon boundaries
  • Track 10-5Expressed sequences and cdna libraries
  • Track 10-6Next-generation sequencing
  • Track 10-7Rna purification & transcriptome enrichment

Phylogenetic analysis is the study of evolutionary relationships among molecules, phenotypes, and organisms. In the context of protein sequence data, phylogenetic analysis is one of the milestone of comparative sequence analysis and has many applications in the study of protein evolution and function.

  • Track 11-1Data collection
  • Track 11-2Inference of homology
  • Track 11-3Sequence alignment
  • Track 11-4Alignment trimming
  • Track 11-5Phylogenetic analysis
  • Track 11-6Protein feature sequences
  • Track 11-7Phylogenetic tree

Robust interpretation of experimental results computing discreet biological domains remains a significant challenge in the face of complex biochemical regulation processes such as organismal versus tissue versus cellular metabolism, epigenetics, and protein post-translational modification. Integration of analyses carried out across multiple measurement ,is an upcoming approach to help address these challenges. This review focuses on select methods and tools for the integration of metabolomic with genomic and proteomic data using a variety of approaches .

  • Track 12-1Pathway or biochemical-ontology-based integration
  • Track 12-2Biological-network-based integration
  • Track 12-3Empirical correlation analysis
  • Track 12-4Data integration
  • Track 12-5Data analysis
  • Track 12-6Networks
  • Track 12-7Biochemical processes

Pharmaceutical research has successfully incorporated a wealth of molecular modelling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process.

  • Track 13-1Molecular modelling
  • Track 13-2Drug discovery
  • Track 13-3Molecular target
  • Track 13-4Molecular interaction
  • Track 13-5Virtual screening
  • Track 13-6Pharmacophore
  • Track 13-7Structure-based drug design