Translational Data Science

Bridging Wet-Lab Insight with Multi-Omics Architecture

Scalable, end-to-end computational frameworks providing advanced inference, single-cell analysis, and structured machine learning pipelines for therapeutic discovery.

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"Data is the bridge between biological complexity and life-saving discovery. We decode the sequence of progress."
Najneen Rejwana

Analytical Capabilities

High-throughput custom analytics mapping cellular mechanisms across diverse biological layers.

Transcriptomics

Bulk and single-cell expression profiles mapping complex cellular heterogeneities.

Seurat v5 Spatial Transcriptomics DESeq2 Watch Overview

Proteomics

Mapping expression dynamics, structural changes, and critical protein-protein interaction networks.

Mass Spec Processing PPI Networks PTM Mapping Watch Overview

Genomics

Predictive in silico modeling, deep learning sequence analysis, and structural validation pipelines.

Biomarker Discovery Predictive Modeling PyTorch Watch Overview

ML / AI Architecture

Predictive in silico modeling, deep learning sequence analysis, and structural validation pipelines.

Biomarker Discovery Predictive Modeling PyTorch Watch Overview

Biostatistics

Rigorous mathematical validation workflows ensuring data integration accuracy and survival significance.

Dimensionality Reduction Survival Analysis Multi-Omics Fusion Watch Overview

Molecular Biology

Mechanistic translational strategies bridging dry-lab discovery loops to actionable wet-lab models.

Target Validation Assay Architecture In Silico Tools Watch Overview

SPIRALONE

Providing industry-grade analytical support for sophisticated multi-omics and computational disease modeling discovery pipelines.

najneenrejwana13@gmail.com

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