Kallyope
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.
A comprehensive, graphical interface solution for the analysis of high-throughput sequencing data.
Partek Flow is a specialized bioinformatics platform designed to democratize high-throughput sequencing (HTS) data analysis by providing a high-performance, browser-based graphical user interface. As of 2026, its technical architecture has evolved to leverage hybrid-cloud scalability, allowing researchers to seamlessly transition between local high-performance computing (HPC) clusters and AWS/Azure/GCP environments. The platform is optimized for multi-omic integration, specifically focusing on the intersection of single-cell RNA-seq, ATAC-seq, and spatial transcriptomics. Unlike command-line-heavy alternatives, Partek Flow employs a 'point-and-click' pipeline builder that captures metadata and ensures complete reproducibility through its internal database schema. Its market position is solidified as a bridge between wet-lab biologists and bioinformaticians, offering pre-built pipelines for alignment, quantification, and statistical analysis (including DESeq2 and Limma integrations). The 2026 version introduces advanced AI-driven cell-type annotation and automated batch-effect correction modules, significantly reducing the bottleneck in large-scale longitudinal clinical studies and drug discovery workflows.
Uses a pre-trained neural network on the Human Cell Atlas to automatically label clusters in scRNA-seq data.
Deciphering the gut-brain axis through AI-driven drug discovery for transformative therapeutics.
Accelerating drug discovery through an end-to-end generative AI pipeline for target identification, molecular design, and clinical trial prediction.
The industry-standard interactive visualization tool for integrated exploration of large-scale genomic datasets.
Unlocking the causal biology of disease through Gemini Digital Twins.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Overlay of transcriptomic expression data onto H&E stained tissue images with sub-cellular resolution.
Direct correlation analysis between chromatin accessibility (ATAC) and gene expression (RNA) from the same cell.
Automatic logging of every parameter, software version, and command-line argument used in a pipeline.
Implementation of Monocle3 and Slingshot within a GUI for pseudotime analysis.
Allows bioinformaticians to inject R or Python code directly into the graphical workflow.
Proprietary optimization of STAR and BWA-MEM for 30% faster processing on x86_64 architectures.
Identifying rare mutations in large tumor datasets that correlate with patient survival.
Registry Updated:2/7/2026
Characterizing T-cell receptor diversity across thousands of individual cells.
Mapping quantitative trait loci (QTL) for crop yield optimization.