Where expertise meets your research goals
Drug discovery is a complex process with many steps. It begins by finding the right targets and identifying groups of patients who will respond well to treatments. Each step has its own challenges and requires specific skills and solutions. At Excelra, our Computational Biology (CB) team blends technical skills with a solid understanding of biology. This allows us to offer clear and helpful insights at every stage of your research.
We assist with finding targets, growing portfolios, data analysis, and developing on the semantic web.
Our solutions help you make decisions faster. They also support your new ideas.
1. Omics Data Analysis and Biomarker Identification
Comprehensive Omics Data Services
- Creating and Using Data Assets: We use the newest NGS technologies to gather, join, and change different omics data. This includes transcriptomics and proteomics. It helps us give important insights for drug discovery. Our team makes sure your data is ready for key decisions, from finding targets to developing models to adjust doses.
- Finding Biomarkers: Our team looks at big public and private datasets to find biomarkers linked to diseases and drugs. We use smart data analysis. We explore pathways and build computer models to help you see how things work. This helps create ideas that lead to success.
Data Management and FAIRification
We make sure your data is correct, secure, and simple to reach. We follow the FAIR guidelines. This means your data is Findable, Accessible, Interoperable, and Reusable..
Key Features:
- Standardizing and managing data
- Managing metadata
- Easy sharing and using of data
Benefits:
- A connected system for your data helps you work together better. It also helps you follow rules and analyze quickly.
2. Data Engineering and Pipeline Development
ETL Pipelines for Efficient Data Processing
Our team makes strong data pipelines. We use them to clean, combine, and change biological data from various file types and platforms. Our skills in cloud solutions help us create a smooth process for adding and mixing data.
Custom Data Analysis Pipelines
We concentrate on making full workflows for NGS data, DEL selection, and other tasks. Our pipelines are flexible and can grow with your needs. They meet industry standards and are built for great performance on platforms such as Google Cloud, Microsoft Azure, and AWS.
Interactive Dashboards and Visualizations
Data-driven decisions require clear information. Our dashboard engineers design easy-to-use and adaptable visualizations with tools such as Power BI, Tableau, and R-Shiny. These tools allow you to spot trends, recognize patterns, and make decisions faster and with confidence.
Semantic Web and Ontology Management
- Knowledge Graphs: We create custom knowledge graphs. These graphs connect different biomedical data. This helps us find new insights.
- Ontology Support: Our team develops and manages specific domain ontologies. This keeps everything consistent and makes it easy to integrate across platforms.
3. AI-Driven Solutions
Machine Learning Applications
We use AI to give important insights. It begins with looking for genomic biomarkers. We also transform unstructured data using Large Language Models (LLMs).
- Explainable AI (XAI): Our clear methods help you see how AI makes predictions. This builds trust and confidence.
Molecular Modeling and Simulations
Our computational chemists use clever techniques. They do virtual screening, scaffold hopping, and molecular dynamics simulations. These methods help us find good candidates, improve compounds, and cut down on mistakes. By using GPU-powered tools, we provide fast and reliable results. This supports your discovery programs.
WHITEPAPER
Omics Data: A Biomedical Asset Driving The Future Of Drug Discovery And Development
Data has become one of the most valuable assets for modern-day drug discovery. Data along with cutting-edge technologies like AI and big data analytics are enabling the drug discovery process in ways never seen before, e.g. soon AI-innovation may be able to save $54 billion in R&D costs annually. Recognizing the value of the data and the Pharma sector may spend more than US$4.5 billion on digital transformation by 2030.
Biomedical data is unique to bio-pharmaceutical sectors, and it can range from omics and clinical data to patient health records. Omics data, especially the next generation sequencing data, is increasing exponentially thanks to recent advances in sequencing technologies. However, it is still underutilized but well-positioned to be leveraged as a data asset that can propel unprecedented growth…
Why Excelra
Expert Team
We have skilled bioinformaticians, data engineers, and biologists on our team.
Customized Solutions
We adjust our methods to meet your unique needs. This way, we make sure the results align with your research goals.
Full Support
We provide help from preparing data to gaining useful insights. Our services help you discover faster.
Let’s Collaborate
Excelra’s Computational Biology team is here to assist you. We can help if you have tough data issues or want to quicken the drug discovery process. Reach out to us today. Let’s talk about how we can help you achieve your goals.
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