Cell Painting Gallery: an open resource for image-based profiling

no code implementations • 3 Feb 2024 • Erin Weisbart, Ankur Kumar, John Arevalo, Anne E. Carpenter, Beth A. Cimini, Shantanu Singh

Image-based or morphological profiling is a rapidly expanding field wherein cells are "profiled" by extracting hundreds to thousands of unbiased, quantitative features from images of cells that have been perturbed by genetic or chemical perturbations.

Reproducible image-based profiling with Pycytominer

1 code implementation • 22 Nov 2023 • Erik Serrano, Srinivas Niranj Chandrasekaran, Dave Bunten, Kenneth I. Brewer, Jenna Tomkinson, Roshan Kern, Michael Bornholdt, Stephen Fleming, Ruifan Pei, John Arevalo, Hillary Tsang, Vincent Rubinetti, Callum Tromans-Coia, Tim Becker, Erin Weisbart, Charlotte Bunne, Alexandr A. Kalinin, Rebecca Senft, Stephen J. Taylor, Nasim Jamali, Adeniyi Adeboye, Hamdah Shafqat Abbasi, Allen Goodman, Juan C. Caicedo, Anne E. Carpenter, Beth A. Cimini, Shantanu Singh, Gregory P. Way

Technological advances in high-throughput microscopy have facilitated the acquisition of cell images at a rapid pace, and data pipelines can now extract and process thousands of image-based features from microscopy images.

A Multi-task Approach to Predict Likability of Books

no code implementations • EACL 2017 • Suraj Maharjan, John Arevalo, Manuel Montes, Fabio A. Gonz{\'a}lez, Thamar Solorio

We investigate the value of feature engineering and neural network models for predicting successful writing.

Binary Classification Feature Engineering +2

Gated Multimodal Units for Information Fusion

9 code implementations • 7 Feb 2017 • John Arevalo, Thamar Solorio, Manuel Montes-y-Gómez, Fabio A. González

The Gated Multimodal Unit (GMU) model is intended to be used as an internal unit in a neural network architecture whose purpose is to find an intermediate representation based on a combination of data from different modalities.

General Classification Genre classification