Rasa Life Science Informatics Services

Kothrud, Pune, Maharashtra

Mostly all clinical research projects give researchers with unsettling work of data (proteomics, genomics and chemicals) collection, integration and analysis. Over the last 9 years, RASA Bioinformatic CRO Lab as bioinformatics services provider or bioinformatics consultancy division has been successfully leading researchers and scientists in meeting their goals in research and development.Our client-base for Bioinformatics services or Bioinformatics Consultancy are from India as well as overseas. With the advancements in computational genomics, transcriptomics, proteomics, metabolomics and techniques like gene mapping, array designing, sequencing, 3D protein modelling, phylogenetics analysis etc., the bioinformatics services or consultancy has turned out to be an increasingly critical application in information mining or data mining. To understand how the cellular activities get altered in different states, the biological information is merged together to create a thorough picture. When used as an important tool, bioinformatics services can help the researchers to expand their understanding of various biological functions and pathways utilizing the computational approach for pattern recognition, machine learning, data mining and finally visualization of the omics data in less time duration. Furthermore, research endeavors in this field incorporate DNA/RNA/protein sequencing, multiple sequence alignment, computational drug discovery, protein structure modelling and simulation, genomic data analysis, gene expression study, protein-protein interaction analysis and many more bioinformatics’ analysis areas. Bioinformatics services also involves development of tools and softwares like genome viewer, gene prediction and protein structure prediction. Due to the cutting edge development in information technology and software engineering, there is a rise of sophisticated algorithms, tools and softwares to perform efficient and rapid analysis.

RASA Bioinformatic Lab’s genome annotation services provides you a closer view on the genomic data analysis in understanding the data along with mapping, annotation and as well as comparative genome analysis of two different strains of same species, understanding its working de novo assembly of the genomic data and furthermore providing de-novo based RNA-Sequence Analysis of the data obtained. The impact of NGS technologies on genomics is far reaching and likely to change the field for years to come. NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed, thereby enabling previously unimaginable scientific achievements and novel biological applications. Among which, genome annotation has remarkably gained the NGS applications, hence providing a huge area for genome annotation services for bioinformatics companies worldwide. But, the massive data produced by NGS also presents a significant challenge for data storage, analyses, and management solutions. RASA Bioinformatic CRO Lab’s genome annotation services use advanced bioinformatics tools which are essential for the successful application of NGS technology. This results in striking impact on genomic research and the entire biological field including mapping, genome annotation and functional predictions along with comparative genomics analysis. Rasa Bioinformatic Lab’s genome annotation services also enlighten the path towards its ability in tackling the unsolved challenges unconquered by previous genomic technologies.

Among the main goals of the Human Genome Project (HGP) was to develop new, better and cheaper tools to identify new genes and to understand their function. One of these tools is gene mapping. Genemapping also called linkage mapping can offer firm evidence that a disease transmitted from parent to child is linked to one or more genes. Gene Mapping also provides clues about which chromosome contains the gene and precisely where the gene lies on that chromosome. Genetic maps are also useful in guiding scientists to the many genes that are believed to play a role in the development of more common disorders such as asthma, heart disease, diabetes, cancer, and psychiatric conditions. Identification of genes is usually the first step in understanding a genome of a species; mapping of the gene is usually the first step of identification of the gene. Gene mapping is usually the starting point of many important downstream studies. Hence we at RASA Bioinformatic CRO Lab’s genome annotation services can also perform gene mapping annotation to discover genes responsible for a disease or disorder or just to get data sufficient enough as the genetic counselling requirements, etc.

Genes encode proteins and proteins dictate cell function. Therefore, the thousands of genes expressed in a particular cell determine what that cell can do. Moreover, each step in the flow of information from DNA to RNA to protein provides the cell with a potential control point for self-regulating its functions by adjusting the amount and type of proteins it manufactures.At any given time, the amount of a particular protein in a cell reflects the balance between that protein’s synthetic and degradative biochemical pathways. On the synthetic side of this balance, recall that protein production starts at transcription (DNA to RNA) and continues with translation (RNA to protein). Thus, control of these processes plays a critical role in determining what proteins are present in a cell and in what amounts. In addition, the way in which a cell processes its RNA transcripts and newly made proteins also greatly influences protein levels. We at RASA Bioinformatic Lab , provide detailed insight for gene expression analysis including the entire Transcriptome analysis (RNA-Seq analysis) and Exome analysis

Transcriptome analysis experiments enable researchers to characterize transcriptional activity (coding and non-coding), focus on a subset of relevant target genes and transcripts, or profile thousands of genes at once to create a global picture of cell function. Gene expression analysis studies can provide a snapshot of actively expressed genes and transcripts under various conditions. Next-generation sequencing (NGS) capabilities have shifted the scope of transcriptomics from the interrogation of a few genes at a time to the profiling of genome-wide gene expression levels in a single experiment. Hence, finding out how to analyze gene expression along with identifying novel transcripts using NGS-based RNA sequencing (RNA-Seq) methods is breakthrough in one of the major applications of NGS technologies. Essential Steps in Trancriptomic Data analysis done at RASA are as follows; identify pairs of ‘incompatible’ fragments that must have originated from distinct spliced mRNA iso-forms. Fragments are then analysed if connected in an ‘overlap graph’ when they are compatible and their alignments overlap in the genome. The iso-forms are then assembled from the overlap graph (minimal approach) and at last the transcript abundance is estimated in FPKMs (Fragments per Kilobase of exon per Million fragments mapped) to study the expression of a particular gene in specific tissue or organ in a defined condition.

Our phylogenetic data analysis services provide computer simulations and empirical data which indicates currently used methods for data analysis such as neighbour joining, minimum evolution, likelihood, and parsimony methods which will produce reasonably good phylogenetic trees when a sufficiently large number of nucleotides or amino acids are used. Phylodynamics is defined as the study of how epidemiological, immunological, and evolutionary processes act and potentially interact to shape viral or bacterial phylogenies. Our phylogenetic data analysis services particularly in Research on viral phylodynamics are focused mainly on transmission dynamics to study how these dynamics impact viral genetic variation. Hence, Our phylogenetic data analysis services Transmission dynamics data can be considered at the level of cells within an infected host, individual hosts within a population, or entire populations of hosts. Many viruses, especially RNA viruses, rapidly accumulate genetic variation because of their short generation times and high mutation rates. The Patterns of viral genetic variation are therefore heavily influenced by how quickly transmission occurs. Although viruses can differ with respect to many phenotypes, phylodynamic studies tend to focus on a limited number of viral phenotypes. These include virulence phenotypes, phenotypes associated with viral transmissibility, cell or tissue tropism phenotypes, and antigenic phenotypes that can facilitate escape from host immunity. Our phylogenetic data analysis services data on Viral phylogenies can therefore be used to investigate important epidemiological, immunological, and evolutionary processes, such as: Epidemic spread Spatio-temporal dynamics including meta-population dynamics Zoonotic transmission Tissue tropism Antigenic drift

On an average, a new drug takes minimum 14 years to come into market;our drug repositioning services’ approach can give your novel molecule or existing molecule a second chance with new target protein (s). This approach can accelerate the introduction of drug molecule into the market along with secondary effects predictions. This program let the new drug to enter into market speedily and that too with less cost. Our drug repositioning services involves compound identification, compound acquisition, preclinical development, preclinical trials and licensing. Rasa’s drug repositioning services approaches are- drug-drug target-disease mapping: rasa bioinformatic cro lab drug repositioning services’ main approach use network based and system biology which includes- pathway or network and target mechanism.here, all the possible chains connecting drugs to disease(s) or target(s), gene-target pathways are used to build rich database. Rule based model and structure base screening: rasa bioinformatic lab drug repositioning services have knowledge based and target based methods for drug re-purposing which includes high-throughput literature analysis and with comprehensive conduction of drug-target association, we have built 970 pharmacological index, for drug re-positioning and approximately 3500 protein targets.

Rasa Bioinformatic CRO Lab offer high quality protein tertiary structures custom modeling services based on your own amino-acid sequences. Combination of modeling and short term simulations under controlled parameters will ensure the reliability of modeled structure for further studies RASA’s protein modeling service comprise of integration of several highly recommended approaches ranging from homology, ab-initio or threading. We can customize and perform modeling as per client. Rasa Bioinformatic Lab are proud to say that we can very successfully model the complex of the proteins. One of the important parts of research in structural biology is to generate a protein structure form the genetic data or the gene.At RASA Bioinformatic Lab, our experts understand the nuances of this and are extremely capable of converting your genetic data into a protein structure using the information provided by the client or curating that information. Our team can successfully translate the genetic sequence into a protein sequence which our experts can then successfully convert into protein structure. Rasa Contract Reaserch Orgnaisation can build protein models using minimal information such as: FASTA sequence, Sequence ID or Protein name.

The term “homology modeling“, also called comparative modeling or sometimes template-based modelling (TBM), refers to modeling a protein 3D structure using a known experimental structure of a homologous protein (the template). We at RASA follow a comparative modelling routine needing three items of input: The sequence of the protein with unknown 3D structure, the “target sequence“, a 3D template is chosen by virtue of having the highest sequence identity with the target sequence. Structural information is always of great assistance in the study of protein function, dynamics, interactions with ligands and other proteins. The “low-resolution” structure provided by homology modeling contains sufficient information about the spatial arrangement of important residues in the protein and may guide the design of new experiments, for example site-directed mutagenesis. Even within the pharmaceutical industry homology modeling can be valuable in structure-based drug discovery and drug design.

The design of new medical drugs possessing desired physical and chemical properties is a challenging task in any pharmaceutical industry. If one goes by the traditional approach, then the designer will need to test a very large number of molecules, and look for the desired pharmacological property that can needs to be present in the drug to be formulated. Therefore it is very useful to have tools that can predict and discriminate the pharmacological activity of a given molecular compound so that the designer needs to do his laboratory experiments in a well directed manner, such that they are they are directed to those molecular groups in which there is a high probability of finding new compounds with desired properties. To speed up the research and development in drug discovery, we at RASA Bioinformatic CRO Lab do High-Throughput Virtual Screening (HTVS). With our prowess in screening multiple compounds (million drug-like), we can yield a list of molecular hits for Pharmacophore (s).

Our Molecular Docking Services aids in providing reliable output hits that can bind to your target, which eases to validate in-silico research with the help of molecular docking and dynamic studies. These HITS can be screened on the basis of ligand or target structure and other properties like physiochemical properties Or in other words, Molecular Docking Services give molecular hits that binds to target(s) with Protein Ligand Docking, Protein Macromolecule & Protein Nucleic Acid Docking. To speed up the research and development in computational drug discovery or CADD, we at RASA do High-Throughput Virtual Screening (HTVS) as a part of our Molecular Docking Services. With our prowess in Molecular Docking Services, we can screen multiple compounds (million drug-like), we can yield a list of molecular hits for your target protein(s). To get best results, we combine pharmacokinetics, pharmacodynamics, chemoinformatics, bioinformatics at one platform in our molecular docking services. RASA’s integrated Molecular docking services aims at optimizing your molecules and our program uses two types of data; one obtained from target- 3D structure, active site prediction service(known-literature, unknown-servers, reference) and second obtained from ligand/molecular HITS-2D /3D structures, data sets

Molecular dynamics (MD) / Molecular simulation, first developed in the late 70s, has advanced from simulating several hundreds of atoms to systems with biological relevance, including entire proteins in solution with explicit solvent representations, membrane embedded proteins, or large macromolecular complexes like nucleosomes or ribosomes. In other words we can say that Molecular dynamics (MD) is simulation and dynamics studies with interacting atoms and/or molecules. Our Molecular Simulation Service & Dynamic Studies Services are an advantage over real experiments because of high cost, complications or too dangerous to perform. Our molecular simulation and dynamic studies services offer specific application of the technique to three main issues (allosteric regulation, docking, and structure refinement) using various molecular dynamic software and tools with efficient and comprehensive molecular dynamic codes. Molecular Simulation Service & Dynamic services of systems having ∼50, 000–100, 000 atoms are now routine, and dynamic studies of approximately 500, 000 atoms are common when the appropriate computer facilities are available. This remarkable improvement is in large part a consequence of the use of high performance computing (HPC), and the simplicity of the basic MD algorithm Molecular dynamics simulations have evolved into a mature computational technique that can be used effectively to understand macromolecular structure-to-function relationships. Present molecular simulation and dynamic studies are close to biologically relevant ones. Information gathered about the dynamic properties of macromolecules is rich enough to shift the usual paradigm of structural bioinformatics from studying single structures to analyze conformational ensembles.

While performing the interaction studies between a protein and a ligand or between to biological entities, it is very important to know the binding site or the active site. RASA’s Target Identification and active site prediction services takes into account the experimental data and then predicts the site accurately using a combination of algorithms. Our target identification and active site prediction services predict the cavity points in a protein using data mining or servers.This prediction further aids in molecular docking services . If the recent trends in computational chemistry and drug discovery are to be studied, it would be seen that personalized medicine has now become fundamental to drug discovery and computational chemistry. Personalized medicine characterizes the diseases at a molecular level to gain better understanding of it. Using the tools and techniques developed by the computational chemist it has become easier to integrate the data generate by such studies and compare it with protein-protein, protein-ligand networks. RASA’s target identification and analysis service builds an approach which is collaborative across genomics, transcriptomics, proteomics, metabolomics, microbiome, pharmacogenomics. Using our superior computational skills we perform the analysis of such data and identify the targets which will then lead on to successful drug discovery protocol.

Quantitative Structural Activity Relationship (QSAR) is frequently used methodology for ligand-similarity based lead identification which quantitatively correlates descriptors with properties (2D and 3D QSAR based on the dimensions of properties used) like physicochemical, biological, toxicity, etc for a set of similar compounds. RASA’s QSAR modelling services will help both computational and experimental chemists to develop reliable QSAR models. These QSAR models generated from our QSAR Modelling services can optimally exploit the experimental data to guide future studies. In addition, our QSAR Modelling services encourage the use of high quality validated QSARs to provide reliable support for experimental study design and regulates decision making. Our QSAR modelling services can be widely applied in academy, industry, and government institutions around the world. It relates chemoinformatics with biology. Recent observations suggest that the structure-based methods & value of statistically-based QSAR approaches help to guide lead optimization. These are starting to be appreciatively reconsidered by leaders of several larger CADD groups. QSAR modelling finds broad application for assessing potential impacts of chemicals, materials, and nano-materials on human health and ecological systems. An area of active 3D QSAR expansion is in the use of predictive models for regulatory purposes by government agencies, where a still growing number of specialized regulatory tools and databases are being developed and validated. As with any scientific discipline, there have been some voices in the community questioning the viability and our QSAR modelling services tries to build newer biologically-based models using HTS data. Also, developing trends on minimizing animal use in biomedical research place additional focus on QSAR as a source of alternative predictors of in vivo effects in both animals and humans.