SciMedian provides comprehensive bioinformatics alternatives, including access to datasets, analytic workflows and algorithms, cloud-computing infrastructure, and scientific support

SciMedian consulting team can provide you comprehensive bioinformatics services of genomic and proteomic data. Also, can assist you to model your operations, tools, data and identify opportunities to streamline your bioinformatics research projects.

Here’s an overview of each area and the services we provide:

Genomics Data Analysis:

• Genomics data analysis involves studying the structure, function, and variations in an organism’s genetic material. Here are some services you can offer:
• Genomic sequencing analysis: Analyzing DNA or RNA sequencing data to identify genetic variants, mutations, or gene expression levels.
• Genome assembly and annotation: Assembling and annotating genomes to identify genes, regulatory regions, and non-coding elements.
• Comparative genomics: Comparing genomes of different organisms to identify similarities, differences, and evolutionary relationships.
• Variant calling and interpretation: Detecting and interpreting genetic variations and their potential impact on health and disease.
• Pathway and network analysis: Analyzing gene interactions, signaling pathways, and biological networks to understand cellular processes and diseases.
• Pharmacogenomics: Studying how genetic variations affect drug response and optimizing personalized medicine approaches.

Proteomic Data Analysis:

• Proteomic data analysis involves studying proteins, their structures, functions, and interactions within a biological system. Here are some services you can offer:
• Protein identification and quantification: Analyzing mass spectrometry data to identify and quantify proteins in a sample.
• Post-translational modification analysis: Identifying and characterizing protein modifications, such as phosphorylation or glycosylation.
• Protein-protein interaction analysis: Studying protein interactions using techniques like yeast two-hybrid or co-immunoprecipitation.
• Structural proteomics: Predicting and analyzing protein structures to understand their functions and drug binding sites.
• Proteogenomics: Integrating proteomic and genomic data to improve genome annotation and identify novel protein-coding regions.
• Biomarker discovery: Identifying protein biomarkers for diseases or drug response prediction.

Healthcare Data Analytics:

• Healthcare data analytics involves analyzing and interpreting large-scale healthcare data to improve patient outcomes, optimize resource utilization, and support decision-making. Here are some services you can offer:
• Electronic Health Record (EHR) analysis: Extracting insights from structured and unstructured EHR data to identify patterns, trends, and disease associations.
• Clinical trial data analysis: Analyzing clinical trial data to evaluate treatment efficacy, identify adverse events, and optimize trial design.
• Predictive modeling and risk stratification: Developing models to predict disease progression, treatment response, or patient outcomes.
• Population health analysis: Analyzing population-level health data to identify disease patterns, risk factors, and intervention strategies.
• Data integration and interoperability: Integrating disparate healthcare data sources to create a unified view for analysis and decision support.
• Data visualization and reporting: Presenting healthcare data in a visual and understandable format for stakeholders and decision-makers.

We tailor our services based on client needs, industry best practices, and the latest advancements in bioinformatics and data analysis techniques.