Classification of Large DNA Methylation Datasets for Identifying Cancer Drivers.
BIGBIOCL an algorithm that can apply supervised machine learning methods to datasets with hundreds of thousands of features for the extraction of alternative and equivalent classification models has been published.

Combining EEG signal processing with supervised methods for Alzheimer's patients classification.
A new procedure for classifying EEG signals has been designed and applyed to real demented and Alzheimer's diseased patients.

A novel method and software for automatically classifying Alzheimer's disease patients by magnetic resonance imaging analysis.
A new paper, method, and software for classifying Magentic Resonance Images has been published in Computer Methods and Programs in Biomedicine.

TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas.
A software tool to search and retrieve TCGA data and convert them in the structured BED format for their seamless use and integration has been released.

MISSEL: a method to identify a large number of small species-specific genomic subsequences and its application to viruses classification.
A new paper, method, and software for identifying multiple species-specific subsequences has been published.


Emanuel Weitschek


Emanuel Weitschek is researcher in Computer Science at the Department of Engineering of Uninettuno University. Additionally, he works with the bioinformatics group of the Institute of Systems Analysis and Computer Science Antonio Ruberti of the Italian National Research Council (IASI - CNR) in Rome. Emanuel graduated in computer engineering and obtained the PhD in Computer Science at the Department of Engineering at Roma Tre University. His research interests are big data science, machine learning, biomedical data analysis, bioinformatics and software engineering. Emanuel is involved in following projects: big data extraction, extension, integration, and classification; clinical data mining; gene expression profile analysis, viruses/bacteria classification with alignment-free techniques, species classification with DNA Barcode sequences, and next generation sequencing (NGS) analysis. Previously, Emanuel was member of the data base group at Roma Tre University working on the GenData 2020 project, whose aim is the design and the development of a distributed and standardized infrastructure for NGS and clinical experiments. Emanuel published more than 40 papers in international peer reviewed journals, conferences, and technical reports. Finally, Emanuel was speaker at several international conferences all over the world (e.g., China, Australia, USA, and Europe), where he met many foreign researchers that are now collaborating with him.

Research Interests


Machine learning
Big data
Bioinformatics
Data mining
Classification
Software Engineering

Contacts


Emanuel Weitschek|Emanuel Weitschek
Department of Engineering|Institute of Systems Analysis and Computer Science
Uninettuno International University|National Research Council
Corso Vittorio Emanuele II, 39|Via dei Taurini, 19
00186 Rome, Italy|00185 Rome, Italy
emanuel[at]iasi.cnr.it|emanuel[at]iasi.cnr.it

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