21 citations · 24 across the 4 of their papers we have counts for
4 papers
PRIMRose: Insights into the Per-Residue Energy Metrics of Proteins with Double InDel Mutations using Deep Learning
Stella Brown, Nicolas Preisig, Autumn Davis +2
Understanding how protein mutations affect protein structure is essential for advancements in computational biology and bioinformatics. We introduce PRIMRose, a novel approach that…
RoseNet: Predicting Energy Metrics of Double InDel Mutants Using Deep Learning
Sarah Coffland, Katie Christensen, Filip Jagodzinski +1
An amino acid insertion or deletion, or InDel, can have profound and varying functional impacts on a protein's structure. InDel mutations in the transmembrane conductor regulator p…
Protein Mutation Stability Ternary Classification using Neural Networks and Rigidity Analysis
Richard Olney, Aaron Tuor, Filip Jagodzinski +1
Discerning how a mutation affects the stability of a protein is central to the study of a wide range of diseases. Machine learning and statistical analysis techniques can inform ho…
Big Holes in Big Data: A Monte Carlo Algorithm for Detecting Large Hyper-rectangles in High Dimensional Data
Joseph Lemley, Filip Jagodzinski, Razvan Andonie
We present the first algorithm for finding holes in high dimensional data that runs in polynomial time with respect to the number of dimensions. Previous algorithms are exponential…