Computational Biology & Medicine

With the increasing availability of data and the improved understanding of system-level interactions in biological systems, computational methods have found many applications in biology and medicine. Research in CISE develops algorithms for long-standing problems in computational biology, such as predicting and characterizing protein interactions, optimizing metabolic networks, and developing computational neuroscience models. Another line of research develops computational methods to advance experimental observation techniques used in biology, from imaging methods to atomic force microscopy. A burgeoning area of research applies Artificial Intelligence (AI) methods to medical data, leading to disease/outcome prediction models and medical decision-making tools.

Cheng & Tian’s Newest Microscopy Advance Published by Nature Communications

Professor Ji-Xin Cheng’s research group has made notable strides in improved chemical  imaging technologies, especially for medical purposes, over the last few years. Their latest, the development of a new type of mid-infrared photothermal (MIP) microscope, was published by Nature Communications in December. The paper, co-authored by collaborator and CISE affiliate Professor Lei Tian, Post-Doctoral Associate […]

Two BU Researchers Receive over $1 Million Each in Funding from the Chan Zuckerberg Initiative

Imagine being able to watch the smallest units of life—like cells and molecules—working together in real time. Seeing and measuring biological processes, a field called dynamic imaging, can help scientists unlock tremendous knowledge for treating diseases, from cancer to Alzheimer’s. In an effort to take biological imaging to the next level, two Boston University College […]

GCR: Collaborative Research: Micro-bio-genetics for Programmable Organoid Formation

This project aims at defining a new area of dynamically-controlled, robot-assisted biological design. A convergent research team consisting of experts in microrobotics, machine learning, and synthetic biology will focus on developing a radically new approach towards analyzing and replicating intricate cellular patterning in mammalian tissues. Not only will this research result in new biological rules, […]

Powerful Updates to Novel Computational Imaging Device Featured in Optica

CISE affiliate Prof. Lei Tian (ECE, BME) and his team, led by PhD students, Yujia Xue (PhD, ECE, 2022) and Qianwan Yang (PhD student, ECE) published their paper “Deep-learning-augmented Computational Miniature Mesoscope” that describes advances to their Computational Miniature Mesoscope (CM2) project. This paper, published in the prestigious journal Optica, presents the CM2  V2, a […]

Paschalidis Shares Health Data Findings in DeLisi Lecture

CISE Director Professor Yannis Paschalidis (ECE, SE, BME, CDS) discussed data-driven reasoning—which he calls “the backbone of engineering systems”—and predictive health analytics as he delivered the Charles DeLisi Distinguished Lecture May 6 to an online audience of about 100 members of the Boston University community. The DeLisi Award and Lecture honors a senior faculty member […]

Machine, Meet Stem Cells

Model organs grown from patients’ own cells may one day revolutionize how diseases are treated. A person’s cells, coaxed into heart, lung, liver, or kidney in the lab, could be used to better understand their disease or test whether drugs are likely to help them. But this future relies on scientists’ ability to form complex […]

Collaborative Research: A Workshop on Pre-emergence and the Predictions of Rare Events in Multiscale, Complex, Dynamical Systems

Although pandemics have threatened human civilization since ancient times, how to predict and prevent them remains one of the most pressing challenges, calling out for innovative insights and practices. Pandemics emerge through incidental ‘perfect storms’: molecular changes in pathogens, gradual trends in climate, subtle shifts in ecological interactions among potential hosts, and even individual behavioral […]

Advancing COVID-19 Drug Development via Network Analysis

CISE Faculty Affiliate Mark Crovella (Prof., CS, Bioinformatics) has teamed up with Simon Kasif (Prof., BME, CS, Bioinformatics) and other CS researchers from across the U.S. to advance COVID-19 drug development via Network Analysis. The researchers are co-developing a machine learning methodology to analyze viral and human protein-protein interaction networks.  Through this work, the researchers […]