BIO SCIENCE
BIO SCIENCE DEVELOPMENT CHENNAI
HOW WE HELP BIO SCIENCE ?
Normally life science applications are developed in traditional technologies like java, .net etc., We develop applications using special frameworks like MEAN stack etc, where you can have unlimited possibilities, applications can be developed in a short duration, maintenance will be less when compared to traditional tech stack, IT infrastructure cost gets reduced. The new technologies are completely scalable and highly interoperable so, that the data can be exchanged between two different types of applications. We are top bio science development company in Chennai.
VISION
Developing custom web and mobile applications for life sciences by leveraging latest technologies which is highly scalable and interoperable Developing smart solutions that will require a minimum IT infrastructure so, that more inventions will happen in Life Sciences. We provide you the best bio science developer in Chennai, India.
GENOMICS
- Genome annotation
- Population genomics
- DNA structure analysis
- Phylogenomics
- Genome variant analysis
- Comparative genomics
- Genome editing
EPIGENOMICS
- DNA methylation
- Genome structure
- Epigenome analysis
- Histone modifications
- Chromatin-state detection and characterization
- DNA methylation deconvolution
- Nucleosome positioning
- DNA modification databases
- Imprinted gene data
TRANSCRIPTOMICS
- Gene expression analysis
- RNA modification analysis
- RNA interference
- Non-coding RNA analysis
- RNA structure analysis
PROTEOMICS
- Protein sequence analysis
- Protein comparison analysis
- Protein structure analysis
- PTM analysis
METABOLOMICS
- Metabolite enrichment analysis
- Transcriptomic and metabolic data integration
- Glycomics
- Metabolite libraries
- Spectral libraries
WHY ISTUDIO
11+ YEARS OF EXPERIENCE
ARE YOU LOOKING FOR BIO SCIENCE DEVELOPMENT SERVICE IN CHENNAI ?
GET THE BEST SOLUTION FOR YOUR BUSINESS
BIOLOGICAL PATHWAY ANALYSIS
- Differential network
- Gene network data
- Metabolic pathways
- Gene network interface
- Protein-protein interaction data
- Metabolic network data analysis
- Gene regulatory network inference
- Host pathogen interaction data
- Signaling pathways
- Phosphorylation network data
- Kinase-substrate relationship inference
- Protein complex prediction
- De novo network enrichment
- Isoform-level network modeling
- Cell cycle
GENOTYPE-PHENOTYPE ANALYSIS
- GWAS analysis
- Linkage analysis
- QTL mapping
- eQTL mapping
- Phenomics
FLUXOMICS
- Constraint based methods
- 13c-fluxomics