OneGenE: One Gene Expansion

Francesco Asnicar

Publications | f.asnicar [at] (Email)


Gene network expansion aims at finding new genes that expand a known gene network. A gene network expansion approach, unlike network inference, require being executed for each gene network of interest. OneGenE is a new approach that iteratively expands every single gene of an organism and combines the results of these single expansions to produce an expansion list for a known gene network.

Protein Function Prediction with Deep Learning

Luca Masera

Publications | luca.masera [at] (Email)


The advent of high-throughput experimental techniques opened the way to genome-wide computational analysis and predictive annotation studies. When considering the joint annotation of a large set of related entities, like all proteins of a certain genome, many candidate annotations could be inconsistent, or very unlikely, given the existing knowledge. We developed a Neural Network framework capable of predicting protein function starting from a minimal set of data, i.e. primary sequence. It exploits Convolutional Layers and a newly designed output layer that incorporates the output structure, in order to guarantee the prediction consistency.