UMass Lowell will resume on-campus instruction, research and campus life for Fall 2020. View the plan for more info.
Our students are given the opportunity to participate in vibrant, novel research projects. The success of any research is shown when the tools, approaches and methods developed can serve as a conduit to finding solutions for specific complex biomedical problems. Generic tools are most often unable to solve complex problems, and the success of most solutions is based in multidisciplinary approach teams.
Our approach is to develop and nurture multidisciplinary teams that will facilitate the sharing of knowledge and will be able to apply their combined computational and biomedical expertise to specific problems. A single group of either biomedical or computational experts alone cannot solve these problems. Computational experts do not have the necessary breadth of knowledge to understand the underlying biological/chemical/biomedical backgrounds of the problem nor the significance or lack thereof of specific discoveries. At the same time, the computational tools and methods being developed by computer scientists are evolving, quite complex to use, and need to be written specifically for problems in the biomedical arena.
A true merging of these diverse fields will encourage the emergence of new tools, methods, algorithms and approaches suitable for new applications in chemistry, genomics and biological sciences. It is only after a tool has been tuned and evolved to solve a particular problem that it can migrate for more general use by scientists.
Our approach to biomedical research is to apply biology, chemistry, computer science, mathematics and statistics expertise to biomedical problems. We define and target applied biomedical problems (from the field of proteomics, genetics and clinical trials) through discussions and presentations of researchers and scientists in the biology, chemistry, and medical fields at UMass Lowell and Mass General Hospital.
Our expertise in computational tools, including visualization, machine learning, data mining, mathematics, statistics and user interfaces is then applied to these problems in collaboration with the applied researchers and scientists. This feedback loop within the activity assures monitoring and oversight of the research activity, in addition to building a general understanding and knowledge of problems and processes to solving complex problems.
The results of this collaborative conduit benefit our students greatly by having them participate in the real time solving of real problems. While we are fulfilling a educational mission we are also providing real solutions to biomedical problems, in addition to an advancing of the integrated tools for specific and general biomedical applications, as well as public domain data sets, techniques and processes.