Robi Tacutu, Ph.D.

Group: Systems Biology of Aging

Department: Bioinformatics & Structural Biochemistry

Group leader

Website

Research interests: Biology/genetics of ageing, longevity and age-related diseases; Prediction of single/multi longevity regulators; Biomarker profiling for healthcare; Bioinformatics; Genomics, epigenomics, transcriptomics; Systems biology; Network biology; Computational biology; Synthetic biology (gene circuit design)

Currently working on

Robi's group is currently studying the relationships between OMIC changes and genetic interventions, pertaining to the field of ageing research. In more detail, the group is using bioinformatic, network biology and machine learning techniques, to investigate genomic, transcriptomic, epigenomic and proteomic data. Applying these methods to learn from the changes that occur with age and from the differences between long- and short-lived mutants, the group aims to develop better ways to predict multi-genetic interventions that can prolong lifespan. Currently the group is focusing on validating its methods for the model organism C. elegans.

Biography

A thorough, analytical and curiosity-driven scientist, with a multidisciplinary background in biology and computer science, Robi received his BSc in computer science from the University Politehnica Bucharest, and his MSc in biochemistry and molecular biology from the University of Bucharest. He has a long-term commitment and interest in the field of biogerontology (since 2005) and received his PhD in 2013 from the Ben-Gurion University of the Negev, in the lab of Prof. Vadim Fraifeld. His thesis was on an ageing-related topic: studying the relationships between aging and age-related diseases with the use of bioinformatics and network biology approaches, and developing computational methods to predict novel genetic determinants of longevity.

Robi continued his research as a postdoc (2011-2015) at the University of Liverpool, in the Integrative Genomics of Ageing Group, led by Dr. Joao Pedro de Magalhaes. Here, he had a role in developing and curating the Human Ageing Genomic Resources collection of databases relevant to ageing research, and was later awarded a EU FP7 Marie Curie fellowship for developing and interrogating an integrated model of ageing to identify causal relationships between hormonal changes and gene expression changes.

Since 2016, Robi leads the Systems Biology of Aging Group (a group of more than 15 people) at the Institute of Biochemistry and focuses on using computational methods in conjunction with large screening datasets to understand the genetic, cellular, and molecular mechanisms behind ageing, longevity and age-related diseases.

Robi has expertise in Biology of Ageing, Bioinformatics, Systems Biology, Network Biology, and Synthetic Biology.

Papers

Year

Matei IV, Samukange VNC, Bunu G, Toren D, Ghenea S, Tacutu RMatei IV et al . Knock-down of odr-3 and ife-2 additively extends lifespan and healthspan in C. elegans. Aging, 2021, 13(undefined).IF=5.60
Constantinescu V, Chiru C, Boloni T, Florea A, Tacutu RConstantinescu V et al . Learning flat representations with artificial neural networks. Applied Intelligence, 2021:2456–2470.IF=5.09
Kulaga AY, Ursu E, Toren D, Tyshchenko V, Guinea R, Pushkova M, Fraifeld VE, Tacutu RKulaga AY et al . Machine Learning Analysis of Longevity-Associated Gene Expression Landscapes in Mammals. International journal of molecular sciences, 2021, 22(3).IF=4.56
Toren D, Yanai H, Abu Taha R, Bunu G, Ursu E, Ziesche R, Tacutu R, Fraifeld VEToren D et al . Systems biology analysis of lung fibrosis-related genes in the bleomycin mouse model. Scientific reports, 2021, 11(1):19269.IF=4.38
Toren D, Kulaga A, Jethva M, Rubin E, Snezhkina AV, Kudryavtseva AV, Nowicki D, Tacutu R, Moskalev AA, Fraifeld VEToren D et al . Gray whale transcriptome reveals longevity adaptations associated with DNA repair and ubiquitination. Aging cell, 2020, 19(7):e13158.IF=7.24
Bunu G, Toren D, Ion CF, Barardo D, Sârghie L, Grigore LG, de Magalhães JP, Fraifeld VE, Tacutu RBunu G et al . SynergyAge, a curated database for synergistic and antagonistic interactions of longevity-associated genes. Scientific data, 2020, 7(1):366.IF=5.54
Bucaciuc Mracica T, Anghel A, Ion CF, Moraru CV, Tacutu R, Lazar GABucaciuc Mracica T et al . MetaboAge DB: a repository of known ageing-related changes in the human metabolome. Biogerontology, 2020, 21(6):763-771.IF=3.77
Martin EC, Sukarta OCA, Spiridon L, Grigore LG, Constantinescu V, Tacutu R, Goverse A, Petrescu AJMartin EC et al . LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers. Genes (Basel), 2020, 11(3):286.IF=3.33
Avelar RA, Ortega JG, Tacutu R, Tyler EJ, Bennett D, Binetti P, Budovsky A, Chatsirisupachai K, Johnson E, Murray A, Shields S, Tejada-Martinez D, Thornton D, Fraifeld VE, Bishop CL, de Magalhães JPAvelar RA et al . A multidimensional systems biology analysis of cellular senescence in aging and disease. Genome biology, 2020, 21(1):91.IF=10.81
Tacutu R, Thornton D, Johnson E, Budovsky A, Barardo D, Craig T, Diana E, Lehmann G, Toren D, Wang J, Fraifeld VE, de Magalhães JPTacutu R et al . Human Ageing Genomic Resources: new and updated databases. Nucleic acids research, 2018, 46(D1):D1083-D1090.IF=11.15
Yanai H, Budovsky A, Barzilay T, Tacutu R, Fraifeld VEYanai H et al . Wide-scale comparative analysis of longevity genes and interventions. Aging cell, 2017, 16(6):1267-1275.IF=7.63
Calvert S, Tacutu R, Sharifi S, Teixeira R, Ghosh P, de Magalhães JPCalvert S et al . A network pharmacology approach reveals new candidate caloric restriction mimetics in C. elegans. Aging cell, 2016, 15(2):256-66.IF=6.71
Fernandes M, Wan C, Tacutu R, Barardo D, Rajput A, Wang J, Thoppil H, Thornton D, Yang C, Freitas A, de Magalhães JPFernandes M et al . Systematic analysis of the gerontome reveals links between aging and age-related diseases. Human molecular genetics, 2016, 25(21):4804-4818.IF=5.34
Yanai H, Budovsky A, Tacutu R, Barzilay T, Abramovich A, Ziesche R, Fraifeld VEYanai H et al . Tissue repair genes: the TiRe database and its implication for skin wound healing. Oncotarget, 2016, 7(16):21145-55.IF=5.17
Toren D, Barzilay T, Tacutu R, Lehmann G, Muradian KK, Fraifeld VEToren D et al . MitoAge: a database for comparative analysis of mitochondrial DNA, with a special focus on animal longevity. Nucleic acids research, 2016, 44(D1):D1262-5.IF=10.16
Craig T, Smelick C, Tacutu R, Wuttke D, Wood SH, Stanley H, Janssens G, Savitskaya E, Moskalev A, Arking R, de Magalhães JPCraig T et al . The Digital Ageing Atlas: integrating the diversity of age-related changes into a unified resource. Nucleic acids research, 2015, 43(Database issue):D873-8.IF=9.20
Wood SH, van Dam S, Craig T, Tacutu R, O'Toole A, Merry BJ, de Magalhães JPWood SH et al . Transcriptome analysis in calorie-restricted rats implicates epigenetic and post-translational mechanisms in neuroprotection and aging. Genome biology, 2015, 16:285.IF=11.31
Tacutu R, Craig T, Budovsky A, Wuttke D, Lehmann G, Taranukha D, Costa J, Fraifeld VE, de Magalhães JPTacutu R et al . Human Ageing Genomic Resources: integrated databases and tools for the biology and genetics of ageing. Nucleic acids research, 2013, 41(Database issue):D1027-33.IF=8.81
Budovsky A, Craig T, Wang J, Tacutu R, Csordas A, Lourenço J, Fraifeld VE, de Magalhães JPBudovsky A et al . LongevityMap: a database of human genetic variants associated with longevity. Trends in genetics : TIG, 2013, 29(10):559-60.IF=11.60
Moskalev AA, Smit-McBride Z, Shaposhnikov MV, Plyusnina EN, Zhavoronkov A, Budovsky A, Tacutu R, Fraifeld VEMoskalev AA et al . Gadd45 proteins: relevance to aging, longevity and age-related pathologies. Ageing research reviews, 2012, 11(1):51-66.IF=5.95
Tacutu R, Shore DE, Budovsky A, de Magalhães JP, Ruvkun G, Fraifeld VE, Curran SPTacutu R et al . Prediction of C. elegans longevity genes by human and worm longevity networks. PloS one, 2012, 7(10):e48282.IF=3.73
Tacutu R, Budovsky A, Yanai H, Fraifeld VETacutu R et al . Molecular links between cellular senescence, longevity and age-related diseases - a systems biology perspective. Aging, 2011, 3(12):1178-91.IF=5.13
Yanai H, Budovsky A, Tacutu R, Fraifeld VEYanai H et al . Is rate of skin wound healing associated with aging or longevity phenotype?. Biogerontology, 2011, 12(6):591-7.IF=3.34
Tacutu R, Budovsky A, Wolfson M, Fraifeld VETacutu R et al . MicroRNA-regulated protein-protein interaction networks: how could they help in searching for pro-longevity targets?. Rejuvenation research, 2010, 13(2-3):373-7.IF=4.22
Tacutu R, Budovsky A, Fraifeld VETacutu R et al . The NetAge database: a compendium of networks for longevity, age-related diseases and associated processes. Biogerontology, 2010, 11(4):513-22.IF=3.41
Wolfson M, Budovsky A, Tacutu R, Fraifeld VWolfson M et al . The signaling hubs at the crossroad of longevity and age-related disease networks. The international journal of biochemistry & cell biology, 2009, 41(3):516-20.IF=4.89
Budovsky A, Tacutu R, Yanai H, Abramovich A, Wolfson M, Fraifeld VBudovsky A et al . Common gene signature of cancer and longevity. Mechanisms of ageing and development, 2009, 130(1-2):33-9.IF=4.18
Tacutu R, Toren D, Ursu E, Bunu G, Bucaciuc Mracica TTacutu R et al . Explaining Health Across the Sciences in Healthy Biological Systems, 2020(5), Springer, Cham:53-78.
de Magalhães JP, Tacutu R. Handbook of the Biology of Aging in Integrative Genomics of Aging, 2016(9), Elsevier, Academic Press:263-285.
Surleac MD, Spiridon LN, TacutuR, Milac AL, Petrescu SM, Petrescu AJSurleac MD et al . Glycosilation in Structural Assessment of Glycosylation Sites Database - SAGS – An Overall View on N-Glycosylation, 2012(1), InTech:3-20.

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