Predicting gene function using similarity learning

Using the Gene Ontology Hierarchy when Predicting Gene Function

The problem of multilabel classification when the labels are related through a hierarchical categorization scheme occurs in many application domains such as computational biology. For example, this problem arises naturally when trying to automatically assign gene function using a controlled vocabularies like Gene Ontology. However, most existing approaches for predicting gene functions solve in...

Learning Similarity Function for Pronunciation Variations

A significant source of errors in Automatic Speech Recognition (ASR) systems is due to pronunciation variations which occur in spontaneous and conversational speech. Usually ASR systems use a finite lexicon that provides one or more pronunciations for each word. In this paper, we focus on learning a similarity function between two pronunciations. The pronunciation can be the canonical and the s...

Enzymes Predicting Function using Structures

Predicting Gene Function from Images of Cells

This dissertation shows that biologically meaningful predictions can be made by analyzing images of cells. In particular, groups of related genes and their biological functions can be predicted using images from large gene-knockdown experiments. Our analysis methods focus on measuring individual cells in images from large geneknockdown screens, using these measurements to classify cells accordi...

Predicting gene function in Saccharomyces cerevisiae

MOTIVATION S.cerevisiae is one of the most important model organisms, and has has been the focus of over a century of study. In spite of these efforts, 40% of its open reading frames (ORFs) remain classified as having unknown function (MIPS: Munich Information Center for Protein Sequences). We wished to make predictions for the function of these ORFs using data mining, as we have previously suc...