D-Index & Metrics Best Publications

Gianluca Pollastri

University College Dublin
Ireland

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name Citations Publications World Ranking National Ranking

Computer Science D-index 35 Citations 6,128 77 World Ranking 7572 National Ranking 27

Overview

What is he best known for?

The fields of study Gianluca Pollastri is best known for:

Protein structure
Amino acid
Bioinformatics

Many of his studies involve connections with topics such as Set (abstract data type) and Template and Programming language. His Set (abstract data type) study often links to related topics such as Programming language. His research is interdisciplinary, bridging the disciplines of Pattern recognition (psychology) and Artificial intelligence. His Artificial intelligence research extends to the thematically linked field of Pattern recognition (psychology). His work on Leverage (statistics) expands to the thematically related Machine learning. In his papers, he integrates diverse fields, such as Artificial neural network and Test set. While working in this field, he studies both Test set and Data mining. Gianluca Pollastri performs integrative Data mining and Overfitting research in his work. With his scientific publications, his incorporates both Overfitting and Artificial neural network.

His most cited work include:

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles (691 citations)
Exploiting the past and the future in protein secondary structure prediction (436 citations)
Porter: a new, accurate server for protein secondary structure prediction (433 citations)

What are the main themes of his work throughout his whole career to date

His Artificial intelligence study frequently draws parallels with other fields, such as Pattern recognition (psychology). His Pattern recognition (psychology) study frequently draws connections to other fields, such as Artificial intelligence. He brings together Biochemistry and Organic chemistry to produce work in his papers. In his research, Gianluca Pollastri undertakes multidisciplinary study on Organic chemistry and Biochemistry. Machine learning and Data mining are two areas of study in which he engages in interdisciplinary research. While working in this field, he studies both Data mining and Machine learning. He integrates several fields in his works, including Protein structure and Protein Data Bank (RCSB PDB). His study deals with a combination of Protein Data Bank (RCSB PDB) and Protein structure. He merges Computational biology with Bioinformatics in his study.

Gianluca Pollastri most often published in these fields:

Artificial intelligence (79.17%)
Biochemistry (60.42%)
Machine learning (50.00%)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles.

Gianluca Pollastri;Darisz Przybylski;Burkhard Rost;Pierre Baldi.
Proteins (2002)

954 Citations

Exploiting the past and the future in protein secondary structure prediction.

Pierre Baldi;Søren Brunak;Paolo Frasconi;Giovanni Soda.
international conference on bioinformatics (1999)

625 Citations

Porter: a new, accurate server for protein secondary structure prediction

Gianluca Pollastri;Aoife Mclysaght.
Bioinformatics (2005)

574 Citations

Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules

Alessandro Lusci;Gianluca Pollastri;Pierre Baldi.
Journal of Chemical Information and Modeling (2013)

457 Citations

Prediction of coordination number and relative solvent accessibility in proteins.

Gianluca Pollastri;Pierre Baldi;Pietro Fariselli;Rita Casadio.
Proteins (2002)

313 Citations

Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity

Catherine Mooney;Niall J. Haslam;Gianluca Pollastri;Denis C. Shields.
PLOS ONE (2012)

261 Citations

The principled design of large-scale recursive neural network architectures--dag-rnns and the protein structure prediction problem

Pierre Baldi;Gianluca Pollastri.
Journal of Machine Learning Research (2003)

249 Citations

Prediction of contact maps by GIOHMMs and recurrent neural networks using lateral propagation from all four cardinal corners.

Gianluca Pollastri;Pierre Baldi.
intelligent systems in molecular biology (2002)

196 Citations

A neural network approach to ordinal regression

Jianlin Cheng;Zheng Wang;G. Pollastri.
international joint conference on neural network (2008)

174 Citations

Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines.

Alessandro Vullo;Oscar Bortolami;Gianluca Pollastri;Silvio C. E. Tosatto.
Nucleic Acids Research (2006)

156 Citations

If you think any of the details on this page are incorrect, let us know.

Frequent Co-Authors

External Links

Personal Website for Gianluca Pollastri