Our precision analysis for each individual patient links data processing algorithms with proprietary algorithms, from which we generate visually rich and easy-to-understand tumor schematics—the BostonGene Molecular-Functional Portrait, or MF Portrait™. The MF Portrait provides the most informed view of the patient’s tumor and potential treatment options.
BostonGene analysis spans the:
Modeling the BostonGene MF Portrait™
BostonGene creates the most comprehensive portrait of the tumor microenvironment and genetic profile for every cancer patient based on RNA and DNA sequencing data. We have developed an automated workflow for analysis of all types of omics data and many more.
The BostonGene MF Portrait enables visualization of a patient’s next-generation sequencing (NGS) data (WGS, WES, RNAseq, scRNAseq) within the landscape of genetic data of patients with a similar diagnosis at a desired level of complexity. The MF Portrait elegantly depicts tumor activity, tumor cellular composition, activity of the immune-microenvironment, and other tumor-associated processes, helping to identify processes that are active or suppressed in the individual patient tumor.
BostonGene built an in-depth biomarker database that includes information about treatment response, prognosis, disease progression, efficacy, and adverse effects. This database is updated daily to provide the most current data available from scientific research.
Clinical data and clinical trials
BostonGene leverages natural language processing (NLP) algorithms—based on machine learning—to systemize, track, search, and learn from clinical data collected on patients, therapies, and clinical trials.
Next-generation sequencing and big data analysis
The BostonGene cloud platform performs large-scale analytics on any next-generation sequencing (NGS) data, including variant calling, transcripts expression, neoantigen prediction, and BCR and TCR repertoires. We follow state-of-the-art approaches and industry best practices to ensure security, privacy, and local compliance in the cloud.
Multiplexed immunofluorescence image processing
BostonGene has developed an automated machine learning based multiplexed immunofluorescence image processing solution for quantitative tissue analysis. This solution performs automated cell typing, spatial distribution and neighboring structures analysis in order to identify tumor and immune-microenvironment interactions.