Semester: Spring 2025

This course will introduce students to micron, nanometer, and sub-nanometer scale imaging-based approaches in experimental, computational and systems biology. Emphasis will be placed on understanding the fundamentals of image formation, processing, and analysis of brightfield, phase-contrast, highly multiplexed, super-resolution, live-cell, cryo-EM, and computational imaging, along with imaging-based spatial transcriptomic methods. Applications of these methods in studying biological phenomena in space and time will also 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.

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Caitlin has been selected as an NIH Pre-Doctoral Trainee on the Cancer Immunology Training Program (CITP) Grant.

Dr. T. Rinda Soong and the Uttam Lab has been awarded the pilot Developmental Research Program (DRP) award from the Hillman Cancer Center Ovarian Cancer SPORE.

An easy-to-use, nonlinear filter for effective background identification in fluorescence microscopy images with dense and low-contrast foreground.

(Preprint on BioRxiv currently under review)

We have received R21 grant award from NCI's ITCR program to develop methods for characterizing mechanobiology of the tumor microenvironment landscape!

New work from our lab pushes forward the performance limits of unsupervised methods in the difficult task of segmenting cells and their nuclei in tissue samples in the context of immunofluorescence imaging and its highly multiplexed counterpart. As part of UNSEG, we have a developed a new perturbed watershed method that stabilizes and improves classical watershed performance for segmenting clustered nuclei.

A microscopy image submitted by Bogdan Kochetov and Rebecca Raphael to a world-wide Micrograph Awards competition held by Microscopy Society of America (MSA) was selected as one of the 25 finalists. It was published on July cover of Microscopy Today (Oxford University Press). It is the fourth image along the diagonal on the cover page linked below.

We were awarded the Biology Data Insights grant by the Chan Zuckerberg Initiative!