In bioinformatics, machine learning (ML) tools are used to solve problems in molecular biology and genetics. In healthy cells, genes — the carriers of hereditary information — are switched “on” or “off” to carry out specific tasks. Bioinformatics researchers can decode DNA using artificial intelligence (AI) to understand why some of these switches occur inappropriately, leading to disease.

Researchers at the University of Illinois Urbana-Champaign have developed a new computational tool that can identify pathways related to diseases, including breast and prostate cancer, using single-nucleotide polymorphisms. SNPs, which refer to mutations in a person’s DNA, are the most common type of genetic variation among people. The researchers hope that the tool can help them discover new pathways that have been previously overlooked.

A newly developed laser source and microscope are helping researchers better understand and search for biomarkers indicative of cancer and other diseases, offering new promise for early detection and treatment plans.

Although the development of secondary cancerous growths, called metastasis, is the primary cause of death in most cancers, the cellular changes that drive it are poorly understood. In a new study, published in Genome Biology, researchers at the University of Illinois Urbana-Champaign have developed a new modeling approach to better understand how tumors become aggressive.

Professor of Molecular and Integrative Physiology Erik Nelson (ACPP) has won a $4.5M Era of Hope Scholar Award from the United States Department of Defense (DoD) Breast Cancer Research Program (BCRP). This prestigious award supports individuals early in their careers who have demonstrated significant potential to effect meaningful change in breast cancer research. Recipients of the Era of Hope Scholar Award are leaders and visionaries in their respective field who go beyond conventional thinking to change the current landscape of breast cancer research and therapy.

For years, scientists have attributed animal behavior to the coordinated activities of neuronal cells and its circuits of neurons, known as the neuronal network (NN). However, researchers are pushing the boundaries in understanding animal behavior through the integration of gene regulation.

Five years ago, a team of computer scientists, biomedical researchers, and bioinformaticians set out to bring the power of collective knowledge to genomic research. Their new publication in PLOS Biology shares the culmination of that effort, an analytical platform that guides researchers through the process of interpreting complex genomic datasets.

A new proof-of-concept study details how an automated system driven by artificial intelligence can design, build, test and learn complex biochemical pathways to efficiently produce lycopene, a red pigment found in tomatoes and commonly used as a food coloring, opening the door to a wide range of biosynthetic applications, researchers report.  

Genomic technologies have the power to transform individual healthcare for the better. But with that power comes responsibility—the responsibility to protect the privacy of the individual and to make ethical choices that respect the rights of communities and populations.

A workshop held at the IGB this summer set out to bridge the gap between research in animal development and research in animal behavior.

The two-day workshop brought together researchers from across the country to discuss how these two fields can borrow ideas from each other.