About the Lab

Scientific research is rapidly becoming a digital, information-driven field resulting in lots of data that’s increasingly more difficult to manage and understand. Bioinformatics strives to adapt the powerful information processing techniques from computer sciences to yield new and exciting discoveries from biological, medical, and health data. Bioinformaticians use powerful computational techniques such as data modeling, machine learning, data mining, and data visualization to analyze and observe biological processes like never before. They play a pivotal role in modern research within both wet laboratories and digital labs.

Bioinformatics at UNO

Bioinformatics at UNO is overseen by recognized experts in the the field whom perform ongoing scientific research with industry support. There are many exciting research opportunities for our students to participate in with our Bioinformatics and Machine Learning (BML) lab, Bioinformatics and Molecular Modeling (BMM) lab, and a wet lab at Research Institute for Children. Additionally, the Computer Science department collaborates with the Chemistry department to share domain knowledge through student presentations. This exchange provides students with practical experience in preparing, presenting, and discussing research with a group of their peers. Ongoing research at UNO includes machine learning applications, protein structure prediction and design.

Scientific Computing

Scientific Computing provides an introduction to the application of computers to scientific inquiry, focusing on theory and practice in simulation, modeling, and visualization approaches used across scientific disciplines.

Bioinformatics

Bioinformatics surveys the effective implementation and application of computer science algorithms towards biological problems. Students will learn to perform mathematical modeling, computation, data-anaylis, structure prediction, and dynamic simulations.

Machine Learning

Machine Learning covers probabilistic techniques used to uncover patterns to predict future data or other outcomes. These concepts have vast applications in bioinformatics, computer vision, robotics, and business intelligence.