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Articles 1 - 3 of 3
Full-Text Articles in Cell and Developmental Biology
Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li
Triphlapan: Predicting Hla Molecules Binding Peptides Based On Triple Coding Matrix And Transfer Learning, Meng Wang, Chuqi Lei, Jianxin Wang, Yaohang Li, Min Li
Computer Science Faculty Publications
Human leukocyte antigen (HLA) recognizes foreign threats and triggers immune responses by presenting peptides to T cells. Computationally modeling the binding patterns between peptide and HLA is very important for the development of tumor vaccines. However, it is still a big challenge to accurately predict HLA molecules binding peptides. In this paper, we develop a new model TripHLApan for predicting HLA molecules binding peptides by integrating triple coding matrix, BiGRU + Attention models, and transfer learning strategy. We have found the main interaction site regions between HLA molecules and peptides, as well as the correlation between HLA encoding and binding …
Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando
Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando
Community & Environmental Health Faculty Publications
Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …
Synergistic Effects Of Nanosecond Pulsed Plasma And Electric Field On Inactivation Of Pancreatic Cancer Cells In Vitro, Edwin A. Oshin, Zobia Minhas, Ruben M. L. Colunga Biancatelli, John D. Catravas, Richard Heller, Siqi Guo, Chunqi Jiang
Synergistic Effects Of Nanosecond Pulsed Plasma And Electric Field On Inactivation Of Pancreatic Cancer Cells In Vitro, Edwin A. Oshin, Zobia Minhas, Ruben M. L. Colunga Biancatelli, John D. Catravas, Richard Heller, Siqi Guo, Chunqi Jiang
Bioelectrics Publications
Nanosecond pulsed atmospheric pressure plasma jets (ns-APPJs) produce reactive plasma species, including charged particles and reactive oxygen and nitrogen species (RONS), which can induce oxidative stress in biological cells. Nanosecond pulsed electric field (nsPEF) has also been found to cause permeabilization of cell membranes and induce apoptosis or cell death. Combining the treatment of ns-APPJ and nsPEF may enhance the effectiveness of cancer cell inactivation with only moderate doses of both treatments. Employing ns-APPJ powered by 9 kV, 200 ns pulses at 2 kHz and 60-nsPEF of 50 kV/cm at 1 Hz, the synergistic effects on pancreatic cancer cells (Pan02) …