Background: Proteins are comprised of one or several building blocks, known as domains. Such domains can be classified into families according to their evolutionary origin. Wherea...
Elon Portugaly, Amir Harel, Nathan Linial, Michal ...
In search for “realistic” bio-inspired computing models, we consider asynchronous spiking neural P systems, in the hope to get a class of computing devices with decidable prope...
Background: Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two met...
Daniel Restrepo-Montoya, Camilo Pino, Luis F. Ni&n...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...
Jason V. Davis, Brian Kulis, Prateek Jain, Suvrit ...