Aging and Disease

Since susceptibility to disease increases with age, studying molecular causes of aging is important. Since human aging is hard to study due to long lifespan and ethical constraints, knowledge about aging needs to be transferred from model species. Thus far, this transfer has been restricted to genomic sequence comparison. But since network topology and genomic sequences can give complementary biological insights, restricting comparison to sequence may limit the knowledge transfer. Hence, network-based across-species comparisons, such as biological network alignment, can be used for this purpose. Milenkovic received an NSF EAGER grant to develop new algorithms for efficient extraction of function from poorly annotated, dynamic, and noisy real-world networks and to use the new algorithms to study molecular processes of human aging from biological networks.

Protein Folding

DNA nucleotide sequence is transcribed into mRNA codon sequence that is translated into protein amino acid sequence, which then folds into 3-dimensional (3D) structure. Most amino acids are encoded by more than one codon. These “synonymous” codons are not used with equal frequency: some are used more often than others. Rarely used codons can slow down translation, which can impact protein folding. Thus, studying the role of rare codons is important. Sequence-based analyses can deal only with amino acids that are close in sequence. Since amino acids that are far apart in sequence can be close in 3D structure, network analyses of known protein structures can further deepen our understanding of protein folding. This collaboration with Prof. P. Clark from Chemistry and Biochemistry is funded by NIH.

Theory-Oriented Research

A variety of theoretic research questions exist behind the projects that Milenkovic lab is actively working on, including: the design of sensitive measures of network topology, network clustering, network comparison and alignment, heterogeneous network analysis, network de-noising, and dynamic network analysis.

Understanding the role of transmission heterogeneity in parasitic worm diseases

Onchocerciasis (river-blindness) and lymphatic filariasis are black-fly and mosquito borne neglected tropical diseases causing blindness and elephantiasis in humans. Onchocerciasis affects approximately 37 million people in Latin America, Africa, and the Arabian peninsula[1,2]. Lymphatic filariasis affects approximately 120 million people worldwide and is endemic in 72 countries[3,4]. The primary control strategy for these diseases consists of mass drug administration and vector control. Mass drug administration programs provide people in infected areas with chemotherapeutic drugs which kill the parasitic worms in patients, while vector control attempts to prevent black-flies and mosquitoes from biting humans through insecticides and bed nets. In our research we are determining which combinations and what durations of these intervention techniques are most effective at eradicating the disease. We are employing high-performance computational resources from Notre Dame's Center for Research Computing (CRC) to make predictions on the time to eradication for these diseases among and across countries. Additionally, we are studying the probability of re-invasion of infection after successful control by using network modelling tools to simulate migration patterns of both human hosts and the disease vectors.

(Photo Credit: William Vanderdecker, Merck)