Maxwell Sherman
About Maxwell Sherman
Maxwell Sherman is a co-founder and CTO who has significantly contributed to cancer research through co-authoring several influential papers on topics ranging from drug response prediction to the identification of cancer-driving mutations using advanced computational models.
Title and Leadership Role
Maxwell Sherman holds the position of Co-Founder & CTO. In his role, he is involved in steering the technological direction of the company and overseeing the development of innovative solutions. His responsibilities often include managing technological strategies, ensuring alignment with business goals, and leading the research and development teams.
Published Research Papers
Maxwell Sherman has co-authored multiple research papers in the field of cancer research. These include 'Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells' (November 9, 2020), 'Interpretation of cancer mutations using a multiscale map of protein systems' (October 1, 2021), 'Biologically informed deep neural network for prostate cancer discovery' (September 22, 2021), and 'Genome-wide mapping of somatic mutation rates uncovers drivers of cancer' (June 20, 2022). Each paper contributes to advancing the understanding and treatment of various forms of cancer using advanced computational models.
Research in Cancer Mutations
Maxwell Sherman has co-authored pivotal papers focusing on cancer mutations. These include 'Multi-resolution modeling of a discrete stochastic process identifies causes of cancer' (May 4, 2021) and 'Interpretation of cancer mutations using a multiscale map of protein systems' (October 1, 2021). His work often uses complex modeling techniques to identify and interpret the mutations driving cancer, providing valuable insights into the disease.
Deep Learning Applications in Cancer Research
Sherman has contributed to research that integrates deep learning with cancer treatment advancements. One notable paper is 'Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells' (November 9, 2020). This research harnesses the power of deep learning models to predict drug responses and synergies, which is crucial for personalized cancer therapies.
Prostate Cancer Discovery
In the realm of prostate cancer, Maxwell Sherman co-authored the paper 'Biologically Informed Deep Neural Network for Prostate Cancer Discovery' (September 22, 2021). This paper discusses the application of deep neural networks to identify biomarkers and potential treatments for prostate cancer, contributing significantly to precision medicine in this area.