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Academic Events

  • Victory Summit – Philadelphia

    Saturday, August 24, 2019

    9:30 AM-3:30 PM

    Philadelphia Marriott Downtown 1201 Market Street Philadelphia, PA 19107

    • Everyone

    Victory Summit – Philadelphia is a free educational event where you will learn from national and regional movement disorder specialists, clinicians and therapists to help you on your path to living well with Parkinson's disease.

    Please register online at or by calling 888.364.6415.

    Complimentary lunch will be served.

    This event is hosted by the Davis Phinney Foundation in partnership with Drexel Neurosciences Institute and the Parkinson Council. Sponsors include Acorda Therapeutics, Lundbeck, Medtronic, the Parkinson's Foundation, Adamas, Boston Scientific, Sunovion and US WorldMeds.

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  • STAR Info Session: Writers Room

    Tuesday, August 27, 2019

    12:00 PM-1:00 PM

    Writers Room

    • Undergraduate Students

    This event is limited to current STAR Scholars.

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  • Fellowships 101

    Tuesday, August 27, 2019

    12:00 PM-1:00 PM

    Disque 109

    • Undergraduate Students
    • Graduate Students
    • Senior Class

    Are you a highly-motivated student with a desire to enhance your academic experience through independent research, service, or leadership?
    Attend an upcoming Fellowships 101 session to learn about how fellowships and competitive external opportunities can help you reach your goals – from international study and internships, to graduate school, and more.
    The session will cover how to identify opportunities that are a good fit and provide you with strategies for deepening your engagement and becoming a more competitive applicant.

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  • Utilizing a Convolutional Neural Network To Predict HIV-1 Tat Biological Functions

    Wednesday, August 28, 2019

    1:00 PM-3:00 PM

    Papadakis Integrated Sciences Building (PISB), Room 104, located on the northeast corner of 33rd and Chestnut Streets.

    • Undergraduate Students
    • Graduate Students
    • Faculty
    • Staff

    BIOMED Master's Thesis Defense

    Utilizing a Convolutional Neural Network To Predict HIV-1 Tat Biological Functions and the Impact of Tat Genetic Variation on Neurocognitive Impairment

    Angela Tomita, Master's Candidate
    School of Biomedical Engineering, Science and Health Systems
    Drexel University

    Will Dampier, PhD
    Assistant Professor
    Department of Microbiology and Immunology
    Drexel University College of Medicine

    Human immunodeficiency virus type 1 (HIV-1) infections have been associated with neurocognitive impairment. However, this cognitive decline occurs at a rate that is specific to individual patients. Evidence suggests that the protein sequence of HIV-1 Tat may have an impact on this rate. The mutations within Tat can affect the biological function of this viral protein. This study proposes to utilize deep learning techniques to perform analysis inference on amino acid mutations changes and their effects on Tat functions.

    To predict biological functions consistent with annotations of the Gene Ontology (GO) Consortium, a convolutional neural network (CNN) was developed and trained on more than 500,000 GO-annotated sequences from the Uniprot Knowledgebase. Analysis was performed on various lengths of Tat protein sequences, considering the prevalence of naturally truncated Tat protein sequences in HIV-1-infected patient patients from the Drexel Medicine CNS AIDS Research and Eradication Study (CARES) cohort. Results of processing truncated Tat subtype B sequences with lengths between 20 and 60 amino acids revealed a decreased sequence similarity with proteins found in the nucleus and an increased sequence similarity with proteins associated with pathogenesis, extracellular regions, and cellular toxicity.

    With the focus of examining which regions of Tat are responsible for its known biological functions, a windowing strategy was implemented. Using 30-mer windows, there was an increase in sequence similarity to proteins associated with ribosomal function and translation for the Tat polypeptide region between positions residues 40 and 80. The CNN achieved an area under the receiver operating curve (AUC) of 0.985 for GO predictions and 0.820 for neurocognitive impairment. The evaluation metric of AUC has been used in several peer-reviewed papers, but it is not an ideal evaluation method. Although the NCI prediction AUC scores are fairly high, there is little to no correlation between the predicted and calculated, actual score using Pearson correlation.

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  • Computer Science Department Student Faculty Forum

    Wednesday, August 28, 2019

    5:00 PM-6:00 PM

    College of Computing & Informatics 3675 Market, Room 1056 Philadelphia, PA 19104

    • Undergraduate Students
    The Computer Science Department will host a Student Faculty Forum for Computer Science and Software Engineering undergraduate students.
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