Nicola Vitulo

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Vitulo, November 6, 2017
Position
Associate Professor
Academic sector
BIO/11 - MOLECULAR BIOLOGY
Office
Ca' Vignal 1,  Floor 1,  Room 1.76
Telephone
0458027982
E-mail
nicola|vitulo*univr|it <== Replace | with . and * with @ to have the right email address.
Curriculum

Prof. Nicola Vitulo graduated in Biology from the University of Padua in 2001 and he obtained his PhD in Biotechnology in 2005 with a thesis on genome sequencing of the psychrophilic and piezophilic bacterium Photobacterium profundum SS9. He has been working as a computational genomics since 2002. During these years he has acquired a great expertise in the field of bioinformatics by developing skills in the field of gene prediction and annotation, analysis of transcriptomics data, comparative genomics and management of genomic data.
The advent of new sequencing technologies (Next Generation Sequencing, NGS) that allow the production of millions of DNA sequences at very low cost and time, has had a very large impact in the study of genomic complexity at the genomic, transcriptomic, epigenetics and metagenomics level,  providing exciting opportunities for the development of new bioinformatics resources for data analysis and management. Prof. Vitulo has worked for many years in the field of genomics developing a strong interest in many aspects of this discipline, focusing especially on the innovations and challenges introduced by NGS technologies.
The main interests and research activities consist in gene annotation prediction, genomic assembly, transcriptomics data analysis, metagenomics data analysis.

Modules

Modules running in the period selected: 18.
Click on the module to see the timetable and course details.

Course Name Total credits Online Teacher credits Modules offered by this teacher
Master's degree in Biotechnology for bioresources and sustainable development Bioinformatics (2021/2022)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2021/2022)   6    3  (Mod. 1)
Master's degree in Molecular and Medical Biotechnology Computational genomics (2021/2022)   6    6 
Master's degree in Biotechnology for bioresources and sustainable development Bioinformatics (2020/2021)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2020/2021)   6  eLearning 3  (Mod. 1)
Master's degree in Molecular and Medical Biotechnology Computational genomics (2020/2021)   6  eLearning 6 
PhD in Biotechnology Synthetic Biology (2020/2021)   4.5  eLearning 1.5 
Master's degree in Biotechnology for bioresources and sustainable development Bioinformatics (2019/2020)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2019/2020)   6  eLearning 3  (Modulo 1)
Master's degree in Molecular and Medical Biotechnology Computational genomics (2019/2020)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2018/2019)   6  eLearning 6 
Master's degree in Molecular and Medical Biotechnology Computational genomics (2018/2019)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2017/2018)   6  eLearning 6 
Master's degree in Molecular and Medical Biotechnology Computational genomics (2017/2018)   6  eLearning 6 
Bachelor's degree in Biotechnology Bioinformatics and biological databases (2016/2017)   6  eLearning 6 
Master's degree in Molecular and Medical Biotechnology Computational genomics (2016/2017)   6  eLearning 6 
Master's degree in Agri-Food Biotechnology Bioinformatics and Protein engineering (2015/2016)   6  eLearning 3  BIOINFORMATICA
Master's degree in Molecular and Medical Biotechnology Computational genomics (2015/2016)   6    6 

 
Research interests
Topic Description Research area
Analisi dati di metagenomica La metagenomica applica una serie di approcci basati su tecnologie di nuova generazione per il sequenziamento del DNA e di metodi bioinformatici per studiare l’intero contenuto genetico di una comunità di microorganismi. Questa competenza consiste nell’utilizzo di metodi bioinformatici per l’analisi di dati di metagenomica generati sia da un approccio basato su amplificazione di un gene marcatore (ad esempio 16S), sia da sequenziamento totale (whole metagenome sequencing). Interdisciplinary
Genomica computazionale La genomica computazionale si occupa dell’analisi e dello studio delle sequenze genomiche mediante l’uso di approcci bioinformatici. Alcune delle attività di cui si occupa la genomica computazionale sono l’assemblaggio di genomi, predizione e annotazione genica, la genomica comparata e l’allineamento di sequenze. Interdisciplinary
Metodi computazionali per l’analisi del trascrittomica La trascrittomica si occupa dello studio e dell’analisi dell’espressione genica. L’analisi del trascrittoma mediante l’utilizzo di sequenziatori di nuova generazione prende il nome di RNA-seq (RNA sequencing). Gli approcci bioinformatici applicati ai dati di RNA-seq permettono di quantificare l’espressione dei geni e di comparare l’espressione genica in condizioni differenti al fine di identificare quali geni sono sovra o sotto regolati nelle diverse condizioni. Interdisciplinary
Projects
Title Starting date
Investigation of cyanobacteria in Lessinia caves: capturing the light in near-dark environments 12/1/20
Viaggio di andata e ritorno al freddo: genomica e trascrittomica comparata nei nototenioidei Antartici e sub-Antartici 10/25/17