activity
20202022
most citedMotif Identification using CNN-based Pairwise Subsequence Alignment Score Prediction

4 citations · 6 across the 7 of their papers we have counts for

collaborators

7 papers

cs.NE2022

EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting

Ethan Jacob Moyer, Alisha Isabelle Augustin, Satvik Tripathi +5

In this work, we highlight our novel evolutionary sparse time-series forecasting algorithm also known as EvoSTS. The algorithm attempts to evolutionary prioritize weights of Long S…

cs.AI2021

2021 Drexel Society of Artificial Intelligence Research Conference

Ethan Jacob Moyer, Yigit Can Alparslan

The 2021 Drexel Society of Artificial Intelligence Research Conference highlights papers focused on a broad set of papers in machine learning. This was our organizations' first ann…

q-bio.BM2021

Functional Protein Structure Annotation Using a Deep Convolutional Generative Adversarial Network

Ethan Moyer, Jeff Winchell, Isamu Isozaki +3

Identifying novel functional protein structures is at the heart of molecular engineering and molecular biology, requiring an often computationally exhaustive search. We introduce t…

q-bio.GN2021★ 4 cited

Motif Identification using CNN-based Pairwise Subsequence Alignment Score Prediction

Ethan Jacob Moyer, Anup Das

A common problem in bioinformatics is related to identifying gene regulatory regions marked by relatively high frequencies of motifs, or deoxyribonucleic acid sequences that often…

cs.LG2021★ 1 cited

Evaluating Online and Offline Accuracy Traversal Algorithms for k-Complete Neural Network Architectures

Yigit Alparslan, Ethan Jacob Moyer, Edward Kim

Architecture sizes for neural networks have been studied widely and several search methods have been offered to find the best architecture size in the shortest amount of time possi…

cs.LG2021★ 1 cited

Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems

Yigit Alparslan, Ethan Jacob Moyer, Isamu Mclean Isozaki +4

In recent years, deep neural networks have had great success in machine learning and pattern recognition. Architecture size for a neural network contributes significantly to the su…

eess.SP2020

Machine learning applications to DNA subsequence and restriction site analysis

Ethan J. Moyer, Anup Das

Based on the BioBricks standard, restriction synthesis is a novel catabolic iterative DNA synthesis method that utilizes endonucleases to synthesize a query sequence from a referen…