A “powerhouse” isn’t a slogan — it’s what you call a group that can actually run an OMICs pipeline on Nextflow, curate a disease landscape from the literature, build a patient-stratification classifier, integrate a knowledge graph, and walk a steering committee through what the data means. All in the same engagement. All on the same team.
Bulk and single-cell RNA-seq, spatial transcriptomics, proteomics and glycoproteomics, metabolomics, WGS/WES, HLA typing — production pipelines on Nextflow, Airflow, Databricks.
Six capability lanes spanning data engineering, OMICs, AI/ML, computational biology, and scientific consulting — designed to be combined as a program demands.
Custom OMICs pipelines on Nextflow, Airflow, and Databricks, supporting RNA-seq, scRNA-seq, spatial transcriptomics, proteomics, metabolomics, WGS/WES, and HLA typing.
Custom curation, ontology management, FAIRification, semantic enrichment, knowledge graphs, and ETL pipelines — turning unstructured public and literature data into queryable, analysis-ready assets.
Machine learning for biomarker discovery, drug response prediction, patient stratification, indication prioritization, and clinical-trial benchmarking. Interpretable models grounded in biological context.
Target identification, prioritization, safety analysis, and dossier building. Disease landscape assessments and knowledge packages. Repositioning, indication expansion, and asset life-cycle management.
Pathway and network analysis, mechanism-of-action elucidation, systems-biology modeling, and integrative multi-OMICs analysis — with biological interpretation that holds up in scientific review.
R-Shiny, Java, and cloud-native applications. Custom databases, BioVisualizer™ dashboards, and visualization via Spotfire, Tableau, R, and Python — built around how your scientists actually work.
Custom curation, literature mining, gold-standard datasets, and refresh pipelines.
ML modeling, statistical analysis, biological interpretation, hypothesis generation.
We’re happy to walk through scope, approach, and timelines for a target ID program, an OMICs pipeline build, a biomarker study, or anything else in the bioinformatics space.
Four recent projects across oncology pipelines, RNA therapeutics, and AI-enabled cohort analysis. Drawn from Excelra’s published case studies.
A U.S.-based oncology-focused biotech needed customized pipelines to handle RNA-Seq, scRNA-Seq, WGS/WES, and HLA typing data at scale[…]
