Dr Luisa Cutillo
Marie Sklodowska-Curie Research Fellow
Department of Neuroscience
Sheffield Institute for Translational Neuroscience
University of Sheffield
385a Glossop Road
Tel: +44 (0) 114 222 22271
Email : email@example.com
My research experience started in Computer Science at the time of my graduation in Mathematics. Then I moved to the Applied Statistics pursuing my PhD. During this time I had the opportunity to be visiting student at the Georgia Institute of Technology and to participate to many European schools and conferences. After my PhD, I switched to the field of Bioinformatics visiting the University of Cambridge, within a short term EMBO fellowship. Soon after, I became member of the Bioinformatics Core of the Telethon Institute of Genetics and Medicine in Naples. As last relevant step of my career I gained a position as assistant professor at the University of Naples Parthenope, at the faculty of Economics. I am now taking the opportunity to build on this multidisciplinary background and apply my skills to a project with potential for translation. I was indeed recently awarded a prestigious Marie S. Curie Fellowship that I am carrying out in the research group of Professor Neil Lawrence, embedded in a truly multidisciplinary environment at the University of Sheffield at SITraN.
During my undergraduate research project at the department of Mathematics of Seconda Università degli Studi di Napoli, I studied algorithms for testing and managing Parallel Architectures. In particular my thesis was carried out during an internship at the Centro di Ricerche per il Calcolo Parallelo ed i Super calcolatori, within the National Research Council (CNR). During this period I focused my research on the management and testing of Beowulf Parallel Architectures.
After my graduation, I shifted my attention to Classification methodologies and I was awarded a grant on “methods and algorithms for multispectral images”, at the Istituto per le Applicazioni del calcolo “MauroPicone” (IAC) within CNR. Throughout this research I learned the basics principles of statistical classification methods, interacting with experts in this field at the CNR.
Subsequently I was enrolled in the Scienze Computazionali ed Informatiche PhD program at the University of Naples Federico II. My PhD work was achieved within an active collaboration with the IAC in Naples, under the supervision of Dr Umberto Amato and Dr Claudia Angelini. During this period I was introduced the real data analysis field, ranging from environmental to biomedical applications. Moreover I developed a deep interest on biological microarrays data analysis, motivated by a fruitful collaboration with the Telethon Institute of Genetic and Medicine (TIGEM) and the Policlinico hospital of Naples, where the biological experiments were carried out. The last part of my PhDproject was explicated during a visiting period at the Georgia Institute of Technology (GATECH), in Atlanta, U.S.A. under the supervision of Professor BraniVidakovic. During this period I learned to handle high frequency data via Wavelets, Multi-scale Statistical Modelling and Denoising.
This interdisciplinary training highlighted to me the importance to integrate different scientific areas of knowledge. In this light, after my PhD I accepted a fellowship at the IAC-CNR whereI joined the project “Sviluppo di metodi di classificazione per iltelerilevamento– Web AGRIcolo per il Telerilevamento WAGRIT” aimed at developing classification methodologies for remote sensing data. At the same time I was awarded a European Molecular Biology Organization (EMBO) Short term fellowship at the Computer Laboratory of the Cambridge University, UK, where I focused on developing variationalbayesian methods for multiple experiments identification of regulatory motifs, under the supervision of Dr Pietro Liò.
After these intense scientific collaborations, I was hired by the TIGEM as statistician responsible for the Bioinformatics core, under the supervision of Dr Diego di Bernardo. TIGEM mission is to understand the mechanism of genetic diseases with the aim of developing preventive and therapeutic strategies. During my exciting and lasting role at the Bioinformatics core, I was involved in many cutting edge bioinformatics projects and had the opportunity to work with world top researchers in the field of bioinformatics and biomedicine. It has been during this period that I had enlightening scientific discussions with Professor Neil Lawrence, visiting TIGEM yearly. During our meetings he provided me with brilliant effective solutions to the detection of genes reacting to a perturbation over time. Moreover,I had the occasion to share with Professor Lawrence his deep knowledge on Gaussian Processes, hence my current MSC project was inspired.
In the last part of my career I obtained a joint position as Assistant Professor (“Ricercatore”) at the University Parthenope of Naples. This gave me the chance to strongly improve my teaching skill and to start new collaborations in the field of mathematics and statistics applied to economy and finance. This interdisciplinary network of collaborations enabled me to transversely apply theoretical methodologies to distinct categories of real data and to publish my works in distinct scientific areas.
My research interests are time series analysis, count data modelling, clustering methods and multiple hypothesis testing procedures. More in general I use to work in the areas of biostatistics and bioinformatics. In particular I am focusing on analysing and modelling RNA-seq data either from bulk or single cell biological experiments.
I am currently supervising one masters student but my project at the University of Sheffield does not include any teaching activity.
I am currently developing my international Marie S Curie project CONTESSA: COuNt data TimE SerieS Analysis.
The aim of this project is to develop methods for analysis of time-series based on count data. For example, detecting significant differences between two count data time series would distinguish between two different models: one in which the two time series are interchangeable, and one in which the second sample is a modification of the first, i.e. the two time series are non-interchangeable. The target of my project broadens to general analysis of count time-series data such as clustering, classification, perturbations inference and machine learning over sequential count data. The project focus on count data sets from ribonucleic acid sequencing (RNA-seq) time course experiments. My project potentially has promising applications in biology, recent examples include high- throughput sequencing, such as RNA-seq and chromatin immunoprecipitation sequencing (ChIP-seq) analyses and more recently Single Cell sequencing.
Pinelli, M; Carissimo, A; Cutillo, L; Lai, C-H; Mutarelli, M; Moretti, M; Veer Singh, M; Karali, M; Carrella, D; Pizzo, M; Russo, F; Ferrari, S,; Ponzin, D; Angelini, C; Banfi, S; Di Bernardo, D. (2016) An atlas of gene expression and gene co-regulation in the human retina.
To appear on Nucleic Acid Research. * (the first 5 co-author are co-first)
Carfora MF, Cutillo L, Orlando A (2014). Modeling the European Central Bank Official Rate: A Stochastic Approach. Journal of Applied Quantitative Methods. V.9, N.3.
Cutillo L, De Feis I, Nikolaidou C, Sapatinas T (2014).Wavelet density estimation for weighted data. Journal of Statistical Planning and Inference 146, 1-19.
Carrella D, Napolitano F, Rispoli R, Miglietta M, Carissimo A, Cutillo L, Sirci F, Gregoretti F, Di Bernardo D (2014). Mantra 2.0: an online collaborative resource for drug mode of action and repurposing by network analysis. Bioinformatics, btu058.
De Cegli R, Iacobacci S, Flore G, Gambardella G, Mao L, Cutillo L, Lauria M, Klose J, Illingworth E, Banfi S, di Bernardo D (2013). Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation. Nucleic Acids Res 41 (2):711-726.
Cutillo L, Carissimo A, Figini S (2012). Network selection: a method for ranked lists selection. PloSone 7 (8):e43678.
Pane LS, Zhang Z, Ferrentino R, Huynh T, Cutillo L, Baldini A (2012). Tbx1 is a negative modulator of Mef2c. Hum Mol Genet 21 (11):2485-2496
Vitiello C, Faraso S, Sorrentino NC, Di Salvo G, Nusco E, Nigro G, Cutillo L, Calabro R, Auricchio A, Nigro V (2009). Disease rescue and increased lifespan in a model of cardiomyopathy and muscular dystrophy by combined AAV treatments.PLoS ONE 4 (3):e5051.
Gennarino VA, Sardiello M, Avellino R, Meola N, Maselli V, Anand S, Cutillo L, Ballabio A, Banfi S (2009). MicroRNA target prediction by expression analysis of host genes. Genome Res 19 (3):481-490.
Cutillo L, Yoon Young J, Ruggieri F, Vidakovic B (2008). Larger Posterior Mode Wavelet
Thresholding and Applications.J Stat Plan Inference, 138:3758-3773
Amato U, Antoniadis A, Cuomo V, Cutillo L, Franzese M, Murino L, Serio C (2008). Statistical cloud detection from SEVIRI multispectral images.Remote Sens Environ, 112: 750-766
Angelini C, Cutillo L, De Canditiis D, Mutarelli M, Pensky M (2008). BATS: A Bayesian user friendly Software for analyzing time series microarray experiments. BMC Bioinf 9(415):1-13
Cutillo L, Amato U (2008). Localized empirical discriminant analysis.Comput Stat Data Anal 52:4966-4978
Allocca M, Doria M, Petrillo M, Colella P, Garcia-Hoyos M, Gibbs D, Kim SR, Maguire A, Rex TS, Di Vicino U, Cutillo L, Sparrow JR, Williams DS, Bennett J, Auricchio A (2008). Serotype-dependent packaging of large genes in adeno-associated viral vectors results in effective gene delivery in mice. J Clin Invest 118(5):1955-1964
Lanza A, Cirillo N, Rossiello R, Rienzo M, Cutillo L, Casamassimi A, de Nigris F, Schiano C, Rossiello L, Femiano F, Gombos F, Napoli C (2008). Evidence of key role of Cdk2 over expression in pemphigus vulgaris. J BiolChem 283(13):8736-8745.
Angelini C, Cutillo L, De Feis I, van der Wath R, and Lio P (2007).Identifying Regulatory Sites Using Neighborhood Species. In: Lecture Notes in Computer Science. LECTURE NOTES IN COMPUTER SCIENCE, vol. 4447, p. 1-10, Springer
Cutillo L, De Marco G, Donnini C (2012). Networks of Financial Contagion.Advanced Dynamic Modeling of Economic and Social Systems. Studies in Computational Intelligence Volume 448, 2013, pp 31-48.
Carissimo A, Cutillo L, De Feis I. Validation of Community robustness. In: CIBB 2015: Computational Intelligence Methods for Bioinformatics and COMPUTATIONAL INTELLIGENCE METHODS FOR BIOINFORMATICS AND BIOSTATISTICS CNR Research Area, Naples (Italy) 10-12 September 2015
Cutillo L, De Feis I, Nikolaidou C, Sapatinas T (2011). Wavelet Density Estimation for Weighted Data. In: CLADAG 2011 short papers usb pen. Pavia, Sept 7-9, 2011
Angelini C., Cutillo L, De Feis I., Liò P., Van Der Wath R. (2008). Combining experimental evidences from replicates and nearby species data for annotating novel genomes . In: AIP Conference Proceedings. Vietrisul Mare, Sept 24-28, 2007