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What We Do
Skills and Practice Areas


  • R

  • Python

  • C++

  • Java

  • Matlab

Other Tech

  • Bioconductor

  • Tensorflow

  • Theano

  • Keras

Bioinformatics Related

  • ChIP-seq

  • RNA-seq

  • ssRNA-seq​

  • Whole Genome-seq

  • CyTOF

With years of data analytics experience in Yale University laboratories, SeqHub understands your research and publication standards. We guarantee clear, publication-worthy analysis delivered in a timely fashion. Our philosophy is to work with you to understand the purpose and field-specific terminology of your research to deliver the most personalized service available.

Math and Statistics

  • Deep learning

  • Signal processsing

  • Sprectral methods

  • Statistical modeling

  • Machine learning

Research Samples

Our team of experts are active academic researchers and contributors to the data science field; the following is a sampling of our publications:

“Ritornello: High fidelity control-free chip-seq peak calling”

“Removal of Batch Effects using Distribution-Matching residual Networks”

“Arpeggio: Harmonic compression of ChIP-seq data reveals protein-chromatin interaction signatures”


“FastPCA” - Random matrix projection approach for very fast principle      components analysis (SVDS in matlab) – publication pending


“Gating Mass Cytometry by deep learning”

In Situ Quantitative Measurement of HER2mRNA Predicts Benefit from Trastuzumab-Containing Chemotherapy in a Cohort of Metastatic Breast Cancer Patients


Germline competency of parthenogenetic embryonic stem cells from immature oocytes of adult mouse ovary.

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