Our paper “Ontology-Based Prediction and Prioritization of Gene Functional Annotations“, which I wrote with Marco Masseroli, has been published in the leading journal IEEE/ACM Transactions on Computational Biology and Bioinformatics (volume 13, issue 2).
This paper is part of a Section on Semantic-Based Approaches for Analysis of Biological Data of this issue of the IEEE/ACM TCBB journal.
Take a look to it!
Our paper “Software Suite for Gene and Protein Annotation Prediction and Similarity Search“, which I wrote with Marco Masseroli, has been published in the leading journal IEEE/ACM Transactions on Computational Biology and Bioinformatics (volume 12, issue 4).
This journal issue is entitled Special Issue on Databases and Softwares in Computational Biology and Bioinformatics, and our paper is related to the Search Computing project.
Take a look to it!
We just got notified of the acceptance of two our scientific papers for presentation and publication at the influential IEEE BIBE 2013, the 13rd IEEE International Conference on Bioinformatics and Bioengineering
One is the article entitled “A Discrete Optimization Approach for SVD Best Truncation Choice based on ROC Curves”, written mainly by me and co-authored by Marco Masseroli, and the other one is entitled “Enhanced Probabilistic Latent Semantic Analysis with Weighting Schemes to Predict Genomic Annotations”, written mainly by Pietro Pinoli and co-authored by me and Marco Masseroli.
The conference will be held in Chania (Crete, Greece, EU) next November.
On May 14th 2012, at Dipartimento di Elettronica e Informazione of Politecnico di Milano, professor Jun Wang from Chinese University of Hong Kong will give a distinguished lecture entitled “The State of the Art of Multiple-winners-take-all Networks: Neurodynamics formulation, Models, and Applications”.
This event is organized by IEEE Computational Intelligence Society Italian Chapter. Here’s the complete announcement:
IEEE CIS Distinguished Lecturer Program
Politecnico di Milano
Dipartimento di Elettronica e Informazione
Sala Seminari 14/05/2012 at 10h00
Piazza L. da Vinci 32, 20133 Milano, Italy
The State of the Art of Multiple-winners-take-all Networks:
Neurodynamics formulation, Models, and Applications
Department of Mechanical & Automation Engineering
Chinese University of Hong Kong
Winner-take-all is a general rule commonly used in many applications such as machine learning and data mining. K-winners-
take-all is a generalization of winner-take-all with multiple winners. Over the last twenty years, many K-winners-take-all neural networks and circuits have been developed with varied complexity and performance. In this talk, I will start with several mathematical problem formulations of the K-winners-take-all solutions via neurodynamic optimization, then present several K winners-take-all networks with reducing model complexity based on our neurodynamic optimization models. Finally, we will
introduce the best one with the simplest model complexity and maximum computational efficiency. Analytical and Monte Carlo simulation results will be shown to demonstrate the computing characteristics and performance. The applications to parallel sorting, rank-order filtering, and information retrieval will be also discussed.
[Per tutti i membri dell’IEEE Computational Intelligence Society]
In questi giorni si vota online per l’elezione del Comitato Amministrativo (AdCom) dell’IEEE Computational Intelligence Society. Tra i candidati, v’invito a votare:
Cesare Alippi (Politecnico di Milano)
Marco Gori (Universita’ di Siena)
Quindi se siete iscritti all’associazione, mi raccomando, votate per loro!
Se conoscete qualcuno che e’ iscritto, invitatelo a fare lo stesso!