Tiziana Sanavia
(RTDa) Research Fellows
- Department of Medical Sciences
- SSD: FIS/07 - applied physics (a beni culturali, ambientali, biologia e medicina)
- ORCID: orcid.org/0000-0003-3288-0631
Contacts
At
- Department of Medical Sciences
- Dipartimento di Scienze Mediche
- Corso di Laurea in Dietistica
- Corso di laurea magistrale Interateneo in Fisica dei sistemi complessi
- Scuola di Specializzazione in Fisica Medica
- Dottorato in Sistemi Complessi per le Scienze della Vita (fino al ciclo 35) - PhD Programme in Complex Systems for Life Sciences (until 35th cycle)
- PhD Programme in Complex Systems for Life Sciences (until 35th cycle)
Curriculum vitae
Selected research products
Pancotti C, Benevenuta S, Repetto V, Birolo G, Capriotti E, SANAVIA T (corresponding), Fariselli P (2021)
A deep-learning sequence-based method to predict protein stability changes upon genetic variations.
https://iris.unito.it/handle/2318/1795390
SANAVIA T (corresponding), Huang C, Manduchi E, Xu Y, Dadi PK, Potter LA, Jacobson DA, Di Camillo B, Magnuson MA, Stoeckert CJ, Gu G (2021)
Temporal Transcriptome Analysis Reveals Dynamic Gene Expression Patterns Driving β-Cell Maturation.
https://iris.unito.it/handle/2318/1795385
Benevenuta S, Pancotti C, Fariselli P, Birolo G, SANAVIA T (2021)
An antisymmetric neural network to predict free energy changes in protein variants.
https://iris.unito.it/handle/2318/1792051
Birolo G, Benevenuta S, Fariselli P, Capriotti E, Giorgio E, SANAVIA T (2021)
Protein Stability Perturbation Contributes to the Loss of Function in Haploinsufficient Genes.
https://iris.unito.it/handle/2318/1782424
Anastasiadou E, Messina E, SANAVIA T, Labruna V, Ceccarelli S, Megiorni F, Gerini G, Pontecorvi P, Camero S, Perniola G, Venneri MA, Trivedi P, Lenzi A, Marchese C (2021)
Calcineurin gamma catalytic subunit ppp3cc inhibition by mir-200c-3p affects apoptosis in epithelial ovarian cancer.
https://iris.unito.it/handle/2318/1805337
Ferretto S, Giuliani I, SANAVIA T, Bottio T, Fraiese AP, Gambino A, Tarzia V, Toscano G, Iliceto S, Gerosa G, Leoni L (2021)
Atrial fibrillation after orthotopic heart transplantatation: Pathophysiology and clinical impact.
https://iris.unito.it/handle/2318/1767316
Anastasiadou E, Messina E, SANAVIA T, Mundo L, Farinella F, Lazzi S, Megiorni F, Ceccarelli S, Pontecorvi P, Marampon F, Di Gioia CRT, Perniola G, Panici PB, Leoncini L, Trivedi P, Lenzi A, Marchese C (2021)
MiR-200c-3p Contrasts PD-L1 Induction by Combinatorial Therapies and Slows Proliferation of Epithelial Ovarian Cancer through Downregulation of β-Catenin and c-Myc.
https://iris.unito.it/handle/2318/1795386
Younes R, Caviglia GP, Govaere O, Rosso C, Armandi A, SANAVIA T, Pennisi G, Liguori A, Francione P, Gallego-Duran R, Ampuero J, Garcia Blanco MJ, Aller R, Tiniakos D, Burt A, David E, Vecchio FM, Maggioni M, Cabibi D, Pareja MJ, Zaki MYW, Grieco A, Fracanzani AL, Valenti L, Miele L, Fariselli P, Petta S, Romero-Gomez M, Anstee QM, Bugianesi E (2021)
Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease.
https://iris.unito.it/handle/2318/1795392
SANAVIA T, Birolo G, Montanucci L, Turina P, Capriotti E, Fariselli P (2020)
Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine.
https://iris.unito.it/handle/2318/1755135
Marioni G, Nicolè L, Cappellesso R, Marchese-Ragona R, Fasanaro E, Di Carlo R, La Torre FB, Nardello E, Sanavia T, Ottaviano G, Fassina A, Marchese-Ragona R (2019)
β-arrestin-1 expression and epithelial-to-mesenchymal transition in laryngeal carcinoma.
https://iris.unito.it/handle/2318/1727951
Huang C, Walker EM, Dadi PK, Hu R, Xu Y, Zhang W, SANAVIA T, Mun J, Liu J, Nair GG, Tan HYA, Wang S, Magnuson MA, Stoeckert CJ Jr, Hebrok M, Gannon M, Han W, Stein R, Jacobson DA, Gu G (2018)
Synaptotagmin 4 Regulates Pancreatic β Cell Maturation by Modulating the Ca2+ Sensitivity of Insulin Secretion Vesicles.
https://iris.unito.it/handle/2318/1727791
Nicolè L, Cappellesso R, SANAVIA T, Guzzardo V, Fassina A (2018)
MiR-21 over-expression and Programmed Cell Death 4 down-regulation features malignant pleural mesothelioma.
https://iris.unito.it/handle/2318/1727950
Nicolè L*, SANAVIA T*, Veronese N, Cappellesso R, Luchini C, Dabrilli P, Fassina A (2017)
Oncofetal gene SALL4 and prognosis in cancer: A systematic review with meta-analysis.
https://iris.unito.it/handle/2318/1727736
McConnell MJ, Moran JV, Abyzov A, Akbarian S, Bae T, Cortes-Ciriano I, Erwin JA, Fasching L, Flasch DA, Freed D, Ganz J, Jaffe AE, Kwan KY, Kwon M, Lodato MA, Mills RE, Paquola ACM, Rodin RE, Rosenbluh C, Sestan N, Sherman MA, Shin JH, Song S, Straub RE, Thorpe J, Weinberger DR, Urban AE, Zhou B, Gage FH, Lehner T, Senthil G, Walsh CA, Chess A, Courchesne E, Gleeson JG, Kidd JM, Park PJ, Pevsner J, Vaccarino FM, Barton AR, Bekiranov S, Bohrson CL, Burbulis IE, Chronister W, Coppola G, Daily K, D', Gama AM, Emery SB, Frisbie TJ, Gao T, Gulyás-Kovács A, Haakenson M, Keil JM, Kopera HC, Lam MM, Lee EA, Marques-Bonet T, Mathern GW, Moldovan JB, Oetjens MT, Omberg L, Peters MA, Pochareddy S, Pramparo T, Ratan A, SANAVIA T, Shi L, Skarica M, Wang J, Wang M, Wang Y, Wierman M, Wolpert M, Woodworth M, Zhao X, Zhou W (2017)
Intersection of diverse neuronal genomes and neuropsychiatric disease: The Brain Somatic Mosaicism Network.
https://iris.unito.it/handle/2318/1731623
Ferraresso S, Aricò A, SANAVIA T, Da Ros S, Milan M, Cascione L, Comazzi S, Martini V, Giantin M, Di Camillo B, Mazzariol S, Giannuzzi D, Marconato L, Aresu L (2017)
DNA methylation profiling reveals common signatures of tumorigenesis and defines epigenetic prognostic subtypes of canine Diffuse Large B-cell Lymphoma.
https://iris.unito.it/handle/2318/1692034
Trojani A, Lodola M, Tedeschi A, Greco A, Di Camillo B, SANAVIA T, Frustaci AM, Mazzucchelli M, Villa C, Boselli D, Morra E, Caroli R (2016)
Transcriptome Analysis Identified Significant Differences in Gene Expression Variability Between WM and IgM-MGUS BM B Cell Clones.
https://iris.unito.it/handle/2318/1805991
Noren DP, Byron LL, Norel R, Rrhissorrakrai K, Hess K, Chenyue WH, Bisberg AJ, Schultz A, Engquist E, Liu L, Lin X, Gregory MC, Xie H, Hunter GAM, Boutros PC, Oleg S, Zachary A, Ambrosini G, Anastassiou D, Baladandayuthapani V, Batten K, Bucher P, Buturovic L, Campion L, Creighton CJ, Chen G, Cheong JH, Di Camillo B, Dreos R, Estrada A, Fatemi SA, Fitzgerald A, Flynn J, Fronczuk M, Gu W, Guha S, Hosseini M, Hung LH, Hunter G, Hwang TH, Kim D, Kim M, Korra J, Krstajic D, Kumar S, Kuh A, Li J, Liu Y, Mcmurray J, Morgan D, Motiwala T, Naegle K, Niemiec R, Oehler VG, Park S, Pattin A, Peabody A, Piraino SW, Regan K, Ronan T, Rościszewski A, Rudnicki W, SANAVIA T, Santhanam N, Shay J, Tang H, Vilar JMG, Wang T, Wright W, Wrzesień M, Xiao G, Xie Y, Yang S, Yang THO, Yang T, Ye J, Yeung KY, Zang X, Zolfaghar K, Żuk P, Norman T, Friend SH, Stolovitzky G, Kornblau S, Qutub AA (2016)
A Crowdsourcing Approach to Developing and Assessing Prediction Algorithms for AML Prognosis.
https://iris.unito.it/handle/2318/1727735
Hill SM, Heiser LM, Cokelaer T, Unger M, Nesser NK, Carlin DE, Zhang Y, Sokolov A, Paull EO, Wong CK, Graim K, Bivol A, Wang H, Zhu F, Afsari B, Danilova LV, Favorov AV, Lee WS, Taylor D, Hu CW, Bayron LL, Noren DP, Bisberg AJ, Mills GB, Gray JW, Kellen M, Norman T, Friend S, Qutub AA, Fertig EJ, Guan Y, Song M, Stuart JM, Spellman PT, Koeppl H, Stolovitzky G, Saez Rodriguez J, Mukherjee S, HPN DREAM Consortium: Al-Ouran R, Anton B, Arodz T, Askari Sichani O, Bagheri N, Berlow N, Bohler A, Bonet J, Bonneau R, Budak G, Bunescu R, Caglar M, Cai B, Cai C, Carlon A, Chen L, Ciaccio MF, Cooper G, Coort S, Creighton CJ, Daneshmand SMH, de la Fuente A, Di Camillo B, Dutta-Moscato J, Emmett K, Evelo C, Fassia MKH, Finkle JD, Finotello F, Gao X, Gao J, Garcia-Garcia J, Ghosh S, Giaretta A, Großeholz R, Guinney J, Hafemeister C, Hahn O, Haider S, Hase T, Hodgson J, Hoff B, Hao Hsu C, Hu Y, Huang X, Jalili M, Jiang X, Kacprowski T, Kaderali L, Kang M, Kannan V, Kikuchi K, Kim DC, Kitano H, Knapp B, Komatsoulis G, Krämer A, Bartosz Kursa M, Kutmon M, Li Y, Liang X, Liu Z, Liu Y, Lu S, Lu X, Manfrini M, Matos MRA, Meerzaman D, Min W, Lorenz Müller C, Neapolitan RE, Oliva B, Obol Opiyo S, Pal R, Palinkas A, Planas Iglesias J, Poglayen D, Sambo F, SANAVIA T, Sharifi Zarchi A, Slawek J, Streck A, Strunz S, Tegnér J, Thobe K, Toffolo GM, Trifoglio E, Wan Q, Welch L, Wu JJ, Xue AY, Yamanaka R, Yan C, Zairis S, Zengerling M, Zenil H, Zhang S, Zi Z (2016)
Inferring causal molecular networks: empirical assessment through a community-based effort.
https://iris.unito.it/handle/2318/1727815
SANAVIA T, Finotello F, Di Camillo B (2015)
FunPat: function-based pattern analysis on RNA-seq time series data.
https://iris.unito.it/handle/2318/1731642
Sinigaglia A, Lavezzo E, Trevisan M, SANAVIA T, Di Camillo B, Peta E, Scarpa M, Castagliuolo I, Guido M, Sarcognato S, Cappellesso R, Fassina A, Cardin R, Farinati F, Palù G, Barzon L (2015)
Changes in microRNA expression during disease progression in patients with chronic viral hepatitis.
https://iris.unito.it/handle/2318/1727794
Zycinski G, Barla A, Squillario M, SANAVIA T, Di Camillo B, Verri A (2013)
Knowledge Driven Variable Selection (KDVS) - a new approach to enrichment analysis of gene signatures obtained from high-throughput data.
https://iris.unito.it/handle/2318/1727727
Aghaeepour N, Finak G, FlowCAP Consortium, Dougall D, Khodabakhshi AH, Mah P, Obermoser G, Spidlen J, Taylor I, Wuensch SA, Bramson J, Eaves C, Weng AP, Iii ES, Ho K, Kollmann T, Rogers W, De Rosa S, Dalal B, Azad A, Pothen A, Brandes A, Bretschneider H, Bruggner R, Finck R, Jia R, Zimmerman N, Linderman M, Dill D, Nolan G, Chan C, Khettabi FE, O', Neill K, Chikina M, Ge Y, Sealfon S, Sugár I, Gupta A, Shooshtari P, Zare H, De Jager PL, Jiang M, Keilwagen J, Maisog JM, Luta G, Barbo AA, Májek P, Vilček J, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, McLachlan GJ, Wang K, Naim I, Sharma G, Nikolic R, Pyne S, Qian Y, Qiu P, Quinn J, Roth A, DREAM Consortium, Meyer P, Stolovitzky G, Saez-Rodriguez J, Norel R, Bhattacharjee M, Biehl M, Bucher P, Bunte K, Di Camillo B, Sambo F, SANAVIA T, Trifoglio E, Toffolo G, Dimitrieva S, Dreos R, Ambrosini G, Grau J, Grosse I, Posch S, Guex N, Keilwagen J, Kursa M, Rudnicki W, Liu B, Maienschein-Cline M, Manninen T, Huttunen H, Ruusuvuori P, Nykter M, Schneider P, Seifert M, Strickert M, Vilar JM, Hoos H, Mosmann TR, Brinkman R, Gottardo R, Scheuermann RH (2013)
Critical assessment of automated flow cytometry data analysis techniques.
https://iris.unito.it/handle/2318/1727799
Sambo F, SANAVIA T, Di Camillo B (2013)
Integration of Genetic Variation as External Perturbation to Reverse Engineer Regulatory Networks from Gene Expression Data.
https://iris.unito.it/handle/2318/1727719
SANAVIA T, Aiolli F, Da San Martino G, Bisognin A, Di Camillo B (2012)
Improving biomarker list stability by integration of biological knowledge in the learning process.
https://iris.unito.it/handle/2318/1731604
Zycinski G, Squillario M, Barla A, SANAVIA T, Verri A, Di Camillo B (2012)
Discriminant functional gene groups identification with machine learning and prior knowledge.
https://iris.unito.it/handle/2318/1804108
Di Camillo B, SANAVIA T, Martini M, Jurman G, Sambo F, Barla A, Squillario M, Furlanello C, Toffolo G, Cobelli C (2012)
Effect of size and heterogeneity of samples on biomarker discovery: synthetic and real data assessment.
https://iris.unito.it/handle/2318/1727817
Di Camillo B, Irving BA, Schimke J, SANAVIA T, Toffolo G, Cobelli C, Nair KS (2012)
Function-based discovery of significant transcriptional temporal patterns in insulin-stimulated muscle cells.
https://iris.unito.it/handle/2318/1727816
SANAVIA T (2012)
Biomarker lists stability in genomic studies: analysis and improvement by prior biological knowledge integration into the learning process.
https://iris.unito.it/handle/2318/180651
Di Camillo B, SANAVIA T, Iori E, Bronte V, Roncaglia E, Maran A, Avogaro A, Toffolo G, Cobelli C (2010)
The Transcriptional Response in Human Umbilical Vein Endothelial Cells Exposed to Insulin: a Dynamic Gene Expression Approach.
https://iris.unito.it/handle/2318/1731644
Courses
- Data Mining: Modellazione Statistica e Apprendimento Automatico dei Dati (FIS0180)
Corso di laurea magistrale Interateneo in Fisica dei sistemi complessi - Fisica 1 (MED3215A)
Corso di Laurea in Dietistica - Machine learning per la fisica medica (FIS0030)
Scuola di Specializzazione in Fisica Medica - SCIENZE BIOMEDICHE 1 (MED3215)
Corso di Laurea in Dietistica - Statistical Inference and Machine Learning
PhD Programme in Complex Systems for Life Sciences (until 35th cycle) - Statistical Inference and Machine Learning
Dottorato in Sistemi Complessi per le Scienze della Vita (fino al ciclo 35) - PhD Programme in Complex Systems for Life Sciences (until 35th cycle)
Research topics
Tiziana Sanavia works on machine (deep) learning approaches for personalized medicine and to analyze molecular data, focusing on Next-generation sequencing data analysis (expertise on whole genome/exome sequencing, epigenomic data and RNA sequencing).
She was visiting scientist at Computational Biology and Informatics Laboratory at Perelman School of Medicine, University of Pennsylvania (Philadelphia, USA), from 2012 to 2013, working on dynamic RNA-seq and epigenomic data for monitoring the development and maturation of pancreatic cells. From 2016 to 2019 she was employed as senior post-doctoral fellow at the Department of Biomedical Informatics, Harvard Medical School (Boston, USA), focusing my research activity on the analysis of whole-genome/exome sequencing data on cancer and neurological diseases. She participated in several international consortia (including NIH and NHGRI programs) and she is currently involved in European Projects related to personalized early risk prediction, prevention, and intervention based on Artificial Intelligence and Big Data technologies.
Research projects
- BRAINTEASER: BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis
- GenoMed4All: Genomics and Personalized Medicine for all though Artificial Intelligence in Haematological Diseases
- Deep learning per la stratificazione e la predizione della progressione della malattia in pazienti con sclerosi laterale amiotrofica
- BRAINTEASER: BRinging Artificial INTelligencE home for a better cAre of amyotrophic lateral sclerosis and multiple SclERosis
- GenoMed4All: Genomics and Personalized Medicine for all though Artificial Intelligence in Haematological Diseases
Activities in agenda
Academic bodies