Bioinformatics

Genome annotation

Genome annotation is the process of attaching the biological information to the sequence regions. Calpine has expertise in identifying the coding and the non coding regions in genome (exons and introns). We also predict the consensus regions, gene and regulatory elements in a genome.

We rely on both curated data sources as well as a range of different software tools for the automated genome annotation pipeline. Ensembl is one of the sources commonly used for genome annotation.

Genomic Functional annotation consists of the identification of below regions.

  • ORF’s and their localization
  • Coding Regions
  • Location Of Regulatory Motifs,
  • Identification of variants and phenotype gene association

Expression Analysis involves.

  • Biochemical Function
  • Biological Function
  • Involved Regulation And Interactions
  • Expression

Diseases Specific Mutation Analysis

For example Cancer:

Testing for the presence of a specific mutation or set of mutations in a human genome (genome sequence) or in a specified region that lead to various types of cancer. Most of the cancers arise as a result of the acquisition of a series of fixed DNA sequence abnormalities, mutations, many of which ultimately confer a growth advantage upon the cells in which they have occurred. There is a vast amount of information available in the published scientific literature about these changes.

There are many databases available as open-source / licensed which contain the information about those cancer mutation and structural variants. The Catalogue Of Somatic Mutations In Cancer (COSMIC) which is a comprehensive database of somatic mutations, is an example.

Drug Discovery Services

Calpine is an experienced service provider to global pharma giants. We have a strong team of researchers specialized in the area of computational medicinal chemistry and provide services in the areas likes Drug Target Identification, de novo ligand designing and lead optimization. We have integrated fragment based discovery solutions to accelerate ‘Hit to Lead’ finding process and provide target focused libraries for diseases like Alzheimer's, Diabetes etc. We have successfully re-purposed drugs for diseases like Alzheimer's. We conduct in-depth study about ligand-protein interaction mechanisms using methods like steered molecular dynamics. We analyze the drug like and lead like properties of compounds by studying their permeability (logBB, Caco-2, MDCK etc), physio-chemical properties (solubility, lipophilicity, stability etc), PKa etc. Our scientists have expertise in many well known drug designing software’s like MOE and Schrodinger maestro. We also perform data curation from various publically available sources.

System Biology

System biology is the study of the interactions between the components of biological systems, and how these interactions give rise to the function and behavior of that system (for example, the enzymes and metabolites in a metabolic pathway). For example in the specific case of diabetes, it has been shown that many factors can contribute to the development of the disease but ultimately these factors lead to hyperglycemia as a final common pathway. The molecular pathways, gene and proteins involved in diabetes need to be characterized for the design of the diabetes model. The development of predictive models using systems biology will help to develop new ways in the management of diabetes from a deeper understanding of the onset and action of diabetes.

Our range of experience and expertise also includes complex diseases pathway characterization and analysis, model building of modules that cells typically use to perform basic biological processes using tools like SBML, cell-designer, hypothesis formation, experimental perturbations, clinical data collection and analysis, model simulations. This will help accurate quantitative prediction of the behavior of the genes and proteins in the underlying networks. Modeling and simulation of metabolic and cellular control pathways are based on either continuous or discrete dynamics. Central to our modeling approach is the paradigm of hybrid models in which discrete events are combined with continuous differential equations to capture the switching behavior that is observed in phenomena such as transcription, protein-protein interactions, and cell division and growth.

Cloud and Grid based NGS

We are experts in handling whole genome sequence data. Our talented team of bioinformaticians and software professionals assembles, annotates, aligns and compares whole genome sequence data using software's like Bwa, GATK, Samtools, Picard, etc. We provide an end-to-end pipeline for NGS analysis. We have also worked on optimization of already discovered pipeline by reducing the time and resource utilization. We detect variants and its prominence using different tools like Variant effect predictor. We also do in-depth study about the frequency of each variant using Vcftoools and our in-house algorithms. We classify each variant based on its association with disease and gene.

We are familiar in handling various file formats in NGS like fastaQ, vcf, bam, sam, bed etc.

Comparative Genomics is an area in the NGS in which we compare the subject genome with a reference genome and comparison of two genomes using open source tools and call the variants. We also have experience in Genome association studies using the tools like PLINK/SWQ.

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