Ksenia Mats has been accepted to the the NIH IRTA post baccalaureate program and will be going to the National Cancer Institute for her post-bac training.

Congrats Ksenia!

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Preprint

Mitochondrial transcript abundance is a standard quality control metric in single-cell RNA sequencing, but fixed percentage thresholds fail to account for the substantial variation in mitochondrial content across cell types and tissues, risking both retention of compromised cells and exclusion of transcriptionally active viable cell populations. We present MitoChontrol, a cell-type-aware probabilistic framework for mitochondrial quality control that models the mitochondrial transcript fraction within transcriptionally coherent clusters as a Gaussian mixture distribution. Compromised-cell components are identified from the upper tail of each cluster-specific distribution, and filtering thresholds are defined as the point at which the posterior probability of cellular compromise exceeds a user-definded confidence value. Applied to controlled perturbation experiments and a pancreatic ductal adenocarcinoma single-cell dataset, MitoChontrol selectively removes transcriptionally compromised cells while preserving biologically elevated but viable populations, outperforming fixed-threshold and outlier-based approaches.

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Thomas will be presenting our work at the 2026 Annual meeting of American Association for Cancer Research (AACR) on graph theoretic spatial heterogeneity analysis of multiplexed immunofluorescence images that allows quantitative differentiation of high grade serous carcionma (HGSC) precursor lesions in the fallopian tube.

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We have received R21 grant award from NCI to study, model and predict advanced adenoma recurrence!

Congratulations Rajdeep for winning the best poster award at the 2026 BioE day!

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BioE day is an Annual research day organized by graduate students in the Department of Bioengineering at Pitt, and draws students and faculty from U Pitt, CMU, WVU and Duquesne Universities.

Caitlin will be giving a talk and a poster at the 2026 Annual Meeting of the Translational Research Cancer Centers Consortium (TRCCC) on her work on MitoChontrol, an adaptive mtRNA filtering of single cell RNA sequencing data.

Semester: Spring 2026

This course introduces students to micron, nanometer, and sub-nanometer scale imaging-based approaches in experimental, computational, and systems biology and bioengineering. Emphasis will be placed on understanding the fundamentals of image formation, processing, and analysis of different imaging modalities along with spatial transcriptomic and proteomic methods. Applications of these methods in studying biological phenomena in space and time will be discussed. Python will be the programming language in which image processing, machine learning, and system biology methods introduced in the course will be implemented. Students are expected to know Python basics. It is also expected that students have a basic understanding of linear algebra and calculus.

The course will also be cross-listed as a Biongineering elective (BIOE 2335) within the Bioimaging track.

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The current version of the syllabus can be found here:

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Congratulations to Danielle on the successful defense of her MS thesis in the Department of Bioengineering, titled "The Underlying Mechanisms Separating Inflammation from Remission in Inflammatory Bowel Disease"!

And for getting accepted to the Integrated Systems Biology PhD program in the School of Medicine!

We are all delighted!