Bioengineering

Deeper understanding of fundamental life sciences, biosensors and microfluidics, bioinformatics, imaging analysis combined with rapid progress in machine learning based data analytics, and high performance parallel computing is contributing and shaping up the field of bioengineering. Our bioengineering team at Lehigh University has made the engineering perspective even more crucial in the area of human health and healthcare. Our focus is development of Single-Wall Carbon Nanotubes (SWCNTs) wrapped with single strands of DNA for medical uses like bio sensing and for drug delivery. The functionality of these SWCNT-DNA hybrids depends of their structure and, ultimately, on the DNA sequence. To find "special" DNA sequences that provides the functional SWCNT-DNA hybrids in vast DNA sequence space (trillions) is an impossible task with conventional experimental and computer simulation methods. We use our expertise in Machine learning/Deep learning algorithms to sift through and identify DNA sequences that can potentially form functional hybrids. We have successfully identified several hundred DNA sequences thus far. We have partnered with National Institute of Standard Technology (NIST) and Memorial Sloan Kettering Cancer Center to further our exploration of data analytics and machine learning models in their application discovery of specific hybrid combinations and compositions. 

Molecular Perceptron: a whole blood profiling array SWCNT-DNA receptor arrays using high-throughput spectroscopy and supervised machine learning algorithms. 

BIOENGINEERING TEAM MEMBERS:

Anand Jagota, Professor, Bioengineering, Lehigh University 

Ming Zheng, Research Chemist, NIST

Daniel A. Heller, Professor, Memorial Sloan Kettering Cancer Center

Arjun Sharma, PostDoctoral Research Associate in Bioengineering, Lehigh University

Yoona Yang, PostDoctoral Research Associate in Bioengineering, Lehigh University