1 code implementation • 5 Oct 2020 • Sam Sinai, Richard Wang, Alexander Whatley, Stewart Slocum, Elina Locane, Eric D. Kelsic
In this work, we implement an open-source Fitness Landscape EXploration Sandbox (FLEXS: github. com/samsinai/FLEXS) environment to test and evaluate these algorithms based on their optimality, consistency, and robustness.
2 code implementations • 9 Dec 2017 • Sam Sinai, Eric Kelsic, George M. Church, Martin A. Nowak
Here we present an embedding of natural protein sequences using a Variational Auto-Encoder and use it to predict how mutations affect protein function.
no code implementations • 2 Dec 2016 • Sam Sinai, Jason Olejarz, Iulia A. Neagu, Martin A. Nowak
Compartments are ubiquitous throughout biology, yet their importance stretches back to the origin of cells.
no code implementations • 4 Oct 2020 • Sam Sinai, Eric D Kelsic
This primer can serve as a starting point for researchers from different domains that are interested in the problem of searching a sequence space with a model, but are perhaps unaware of approaches that originate outside their field.
no code implementations • 18 Nov 2022 • Lauren Berk Wheelock, Stephen Malina, Jeffrey Gerold, Sam Sinai
The ability to design and optimize biological sequences with specific functionalities would unlock enormous value in technology and healthcare.
no code implementations • 4 May 2023 • David H. Brookes, Jakub Otwinowski, Sam Sinai
Here we demonstrate that minimizing contrastive loss functions, such as the Bradley-Terry loss, is a simple and flexible technique for extracting the sparse latent function implied by global epistasis.
no code implementations • 9 Nov 2023 • Farhan Damani, David H Brookes, Theodore Sternlieb, Cameron Webster, Stephen Malina, Rishi Jajoo, Kathy Lin, Sam Sinai
A common scenario involves using a fixed training set to train models, with the goal of designing new samples that outperform those present in the training data.