جست‌وجوی استاد و پژوهشگر

Damiano Piovesanمشاهده پروفایل

دانشیار

• Protein function prediction
• Intrinsically disordered proteins (IDPs)
• Machine learning in bioinformatics
• +۵ مورد دیگر

Damiano Piovesan is Associate Professor in Bioinformatics (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua , Italy. Since March 2022 he has held this rank, having previously served as Assistant Professor (2022) and PostDoc researcher (2019) in the same department. Education 2013 – PhD in Biotechnology, Pharmacology and Toxicology, University of Bologna 2009 – MSc in Bioinformatics, University of Bologna 2007 – BSc in Biotechnology, University of Bologna Research Focus Piovesan’s research integrates machine-learning approaches with structural bioinformatics to advance understanding of intrinsically disordered proteins (IDPs) and protein function prediction . He develops widely used resources such as MobiDB for disorder annotation, DisProt for functional curation of disordered regions, and RING for residue interaction networks. Additional interests include tandem repeat proteins , cancer-related IDP targets , and community benchmarking initiatives (CAFA, CAID, CAGI). Publication Trends His 2024–2025 output is dominated by updates to flagship databases ( InterPro , DisProt , MobiDB ), next-generation disorder predictors leveraging deep learning ( PredIDR , MobiDB-lite 4.0 ), and large-scale genomics challenges ( CAGI6 ). Across the decade, recurring themes include methodological advances in disorder prediction, creation of interoperable bioinformatics platforms, and rigorous benchmarking to ensure community-wide reliability. Scientific Awards No specific awards are listed in the provided materials. Advising & Grants No individual students or grant details are explicitly supplied; however, his leadership in multi-institutional consortia (e.g., InterPro, DisProt, CAFA) implies substantial supervisory and funding coordination roles. Labs & Teams Piovesan is affiliated with the BioComputingUP Lab ( https://biocomputingup.it/ ) at the University of Padua, a hub for computational biology and bioinformatics tool development.

• Structural Bioinformatics
• Protein Stability Prediction
• Machine Learning in Biology
• +۳ مورد دیگر

Emidio Capriotti is an Associate Professor at the Department of Pharmacy and Biotechnology, University of Bologna. He leads the Second Cycle Degree in Bioinformatics and holds a PhD in Physical Sciences. His research focuses on predicting protein stability changes due to genetic variations using machine learning, with applications in personalized medicine. He develops tools like DDGun and PhD-SNPg for variant interpretation. Teaching includes courses on Bioinformatics, Biophysics, and Lab Techniques for Bioinformatics. His work bridges computational methods and biological problems, particularly in cancer genomics and protein structural analysis. Education: PhD in Physical Sciences from the University of Bologna. Research interests include structural bioinformatics, protein folding, and the interplay between genomic variations and disease. He collaborates with initiatives like CAGI challenges and ELIXIR-IT to advance genomic data infrastructure. Publications emphasize protein stability prediction, federated learning in clinical settings, and benchmarking computational methods. His lab contributes to open-source tools and standards for reproducible machine learning in biology.

• Genomics
• Transcriptomics
• Network Biology
• +۷ مورد دیگر

Pasquale Luca Curci is a Researcher at the Institute of Biosciences and BioResources (IBBR), part of the National Research Council of Italy (CNR) in Bari. His work focuses on integrating large-scale genomic and transcriptomic datasets to uncover biological mechanisms in plants, particularly in crops like durum wheat and artichoke. His research interests span genomics, transcriptomics, and network biology, with a strong emphasis on nitrogen use efficiency, gene regulatory networks, and plant stress responses. He employs systems biology approaches to identify key genes and regulatory elements involved in plant development and adaptation. The analysis of his recent publications reveals a consistent focus on plant genomics, particularly in durum wheat and Cynara species. His work integrates omics data to understand gene function, stress responses, and evolutionary relationships. Key themes include nitrogen metabolism, microRNA regulation, chloroplast genomics, and cross-species network analysis. He has led and coordinated multiple national and international research collaborations with institutions in Belgium, Sweden, Spain, France, and Italy, focusing on gene function discovery, nitrogen efficiency, and germplasm characterization. Integrative network analysis for gene function discovery in wheat (with BASF Agricultural Solutions, Belgium) Cross-species network biology in plants (with SweTree Technologies, Sweden) Transcriptomics and regulatory networks in durum wheat (with Sequentia Biotech SL, Spain) Phenotypization and genomic analysis of durum wheat (with Alma Mater Studiorum, Bologna) Asparagine synthetase genes in durum wheat (with INRA-CNRGV, France) He has contributed to the development of genomic resources for Cynara and has published extensively on chloroplast genomics, transcriptomics under nitrogen stress, and genetic diversity in vegetable crops. His work supports crop improvement and sustainable agriculture through advanced molecular tools.

Alfredo Bensoمشاهده پروفایل

استاد

• Bioinformatics
• Systems Biology
• Artificial Intelligence
• +۱۶ مورد دیگر

Alfredo Benso is a Full Professor in the Department of Control and Computer Science (DAUIN) at the Polytechnic University of Turin, where he is also a member of the Interdepartmental Center PolitoBIOMed Lab - Biomedical Engineering Lab. He has been continuously involved in the Doctoral College for Computer and Systems Engineering since 2008, guiding PhD education across numerous cycles. His academic roles span teaching and research leadership in bioinformatics, systems biology, and computer engineering. Research interests: Bioinformatics and computational biology Systems biology and gene regulatory networks Artificial intelligence and machine learning in biomedicine Molecular modeling and multiscale simulation Biological database systems and data integration Health informatics and public health modeling His recent publications reflect a strong trend in applying AI and machine learning to biological and medical challenges, including protein function prediction, Alzheimer’s and Multiple Sclerosis modeling, food fraud detection, and viral genome analysis. These works span journals and conferences in bioinformatics, computational biology, and biomedical engineering, demonstrating interdisciplinary innovation. Scientific Awards: BIOINFORMATICS 2014 BEST PAPER AWARD (INSTICC, United Kingdom) Advising and Grants: He supervises PhD students, including Sofia Ostellino, and leads major research initiatives such as the BIGMECH (2023–2025) and FISHUB (2016–2018) projects. He has served as Scientific Director for collaborative agreements with public administrations and as Principal Investigator on EU, national (PRIN), and regional research grants focused on bioinformatics, space systems, and reliable digital technologies. Labs and Teams: He is a key member of the SBG - System Biology Group (DAUIN) and contributes to PolitoBIOMed Lab, fostering collaborative research in biomedical engineering and computational biology.

• Biochemistry
• Bio-energy with carbon capture and storage
• Bioinformatics
• +۵ مورد دیگر

Angela Re is an Associate Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, specializing in computational biology and bioinformatics with applications spanning sustainable energy, healthcare, and environmental systems. Her research focuses on two primary domains: Data-driven biomolecular space representations through database development and network analysis tools Computational biology applied to prokaryotic/eukaryotic organisms across diverse ecosystems and industrial contexts Her work integrates bioinformatics, biophysics, and medical informatics to address UN Sustainable Development Goals including climate action (13), affordable clean energy (7), and good health (3). Recent publications (2024-2025) reveal strong thematic convergence in microbiome analysis, metabolic engineering, and protein function prediction. Key trends include machine learning applications for genomic data interpretation, sustainable chemical production using engineered microorganisms, and gut microbiota dynamics in neurodegenerative disease models. She actively mentors doctoral researchers and secures competitive funding: Supervised PhD students: Giulia Usai (2020-2024) and Luca Ricci (2019-2023) Current projects: PROT-mBIOMA-AD (Scientific Responsible, 2023-2025) on Alzheimer's gut microbiota, PNRR NEST Spoke 3 (2022-2025) for energy transition, and Solvay contract for battery membrane development Her research operates within the Institute of Fundamental Physics and Materials for Nanotechnology (DISAT), driving computational approaches to sustainable biotechnology challenges.

• Bioinformatics
• Systems Biology
• Deep Learning
• +۶ مورد دیگر

Gianfranco Michele Maria Politano is an Associate Professor at the Department of Control and Computer Science (DAUIN) at Polytechnic University of Turin, with affiliations to the College of Computer, Film and Mechatronics Engineering and College of Biomedical Engineering. His research focuses on Bioinformatics, Systems Biology, and Deep Learning applications in health. Research trends span computational modeling of biological systems, protein function prediction using machine learning, and public health analysis of disease burdens (influenza, rectal cancer, and COVID-19). He also investigates gene regulatory networks and microRNA roles in inflammation. His teaching includes Bioinformatics and Internship courses for Computer Engineering and Aerospace Engineering students since 2019. He supervises PhD student Sofia Ostellino on computational solutions for disease monitoring and has secured research grants for biostatistics projects like DIDES (exotic animal diagnostics) and rectal cancer ultrasound staging. Notable projects : DIDES (2020), Feasibility study for rectal cancer diagnostics (2021) Patents : Computerized culture protocols for biomanufacturing, Simulation of biological ontogeny

Maximilian Millerمشاهده پروفایل

پژوهشگر ارشد

• Variant Effect Prediction
• Metagenome Analysis
• High-Performance Computing
• +۳ مورد دیگر

Maximilian Miller is a Research Fellow at the BrombergLab , affiliated with the School of Environmental and Biological Sciences and Department of Biochemistry and Microbiology. He focuses on variant effect prediction , metagenome analysis , and high-performance computing infrastructure. PhD in Bioinformatics (2018) from Technical University Munich MSc and BSc in Bioinformatics (2012, 2009) from Ludwig-Maximilians-University Munich / Technical University Munich His research employs machine learning to understand how protein mutations relate to disease , with applications in precision medicine and microbiome studies . He develops tools like clubber for cluster computing and funtrp for functional tuning analysis. The most recent 15 articles span variant interpretation , metagenomic pipelines , and computational method assessment across bioinformatics , protein science , and environmental microbiology . Scientific recognition includes the CAMDA Fellowship for ISMB/ECCB 2019. His work addresses challenges in metagenome recovery (e.g., Deepwater Horizon oil-spill study), taxonomic vs. functional shifts , and predictor performance benchmarks through the Critical Assessment of Genome Interpretation (CAGI) framework.

Chengsheng Zhuمشاهده پروفایل

پژوهشگر ارشد

• Microbiome Research
• Function Prediction
• Machine Learning
• +۳ مورد دیگر

Chengsheng Zhu serves as a Research Fellow in the Department of Biochemistry and Microbiology at Rutgers University's School of Environmental and Biological Sciences, conducting computational microbiome research within the BrombergLab. His work focuses on developing analytical tools for large-scale microbial genomic data to understand microbe-environment interactions with applications in bioremediation, human health, and climate science. His academic background includes: Ph.D. in Microbiology and Molecular Genetics (2017), Rutgers, the State University of New Jersey M.Sc. in Biology (2010), Central Michigan University B.Sc. in Biology (2006), Fudan University Research centers on microbiome dynamics, machine learning applications for function prediction, and computational genomics. He investigates how microbes reshape environments ranging from human guts to extraterrestrial samples, with emphasis on detoxification processes and health implications. Current work develops high-precision tools for microbial community analysis at massive scales. Publications reveal strong computational focus across diverse environments—human gut, urban subways, snowpacks, and waste treatment systems—with recurring themes in functional annotation, microbial diversity assessment, and bioinformatics tool development for big data challenges. No scientific awards were documented in the source materials. Advising and grant activities aren't specified in available information, though his BrombergLab affiliation indicates active participation in collaborative research projects. He contributes to the BrombergLab's mission of advancing computational approaches to microbiome analysis, particularly for environmental and biomedical applications requiring large-scale data processing.

Emanuela Leonardiمشاهده پروفایل

استادیار

• Personalized Medicine
• Neurodevelopmental Disorders
• Non-globular domains in human diseases
• +۳ مورد دیگر

Emanuela Leonardi is an Assistant Professor (tenure track) in Biochemistry (SSD BIO/10) at the Department of Biomedical Sciences , University of Padua (Italy) , where she has held this position since October 2022. Her research focuses on Personalized Medicine , Neurodevelopmental Disorders , and Non-globular Domains in Human Diseases . PhD in Bioscience and Biotechnology (Curriculum: Biochemistry and Biophysics), University of Padova, 2012 MSc in Molecular Biology , University of Padova, 2008 BSc in Molecular Biology , University of Padova, 2005 Degree in Biomedical Laboratory Technician , University of Padova, 1998 Her recent publications highlight expertise in genetic variant interpretation , neurodevelopmental disorder diagnostics , and bioinformatics analysis of intrinsically disordered proteins , particularly through contributions to the CAGI (Critical Assessment of Genome Interpretation) and DisProt databases. Key collaborations span Human Genetics , Nucleic Acids Research , and computational genomics consortia.

Andrea Secchiمشاهده پروفایل

استاد

• Supramolecular Chemistry
• Molecular Recognition
• Nanoscience
• +۴ مورد دیگر

Andrea Secchi is a Full Professor in the Department of Chemical, Life and Environmental Sustainability Sciences at the University of Parma. He holds a Master's in Chemistry (1992) and a PhD in Chemical Sciences (1995) from the University of Parma. His research focuses on supramolecular chemistry, molecular recognition, and nanoscience, particularly involving calixarene-based systems, molecular machines, and functional nanomaterials. He has supervised over 60 theses and 8 PhD students in chemistry and materials science. His work bridges organic synthesis, materials science, and bioapplications, with over 94 peer-reviewed articles and a citation count exceeding 2,800. Education: PhD in Chemical Sciences, University of Parma (1995) Master's in Chemistry, University of Parma (1992) Research interests include calixarene functionalization for molecular machines, hybrid organic-inorganic nanomaterials, and NIR dye-plasmonic material interactions. His nanomaterials research spans gold/silver nanoparticles, magnetic nanoparticles, and self-assembled monolayers. Recent work explores applications in biosensing, drug delivery, and environmental analysis. Teaching roles since 2005 include courses in Physical Methods in Organic Chemistry, Organic Chemistry of Materials, and Environmental Chemistry at both undergraduate and graduate levels. Administrative roles include Chair of the Chemistry Course of Study Board, member of the Department Safety Committee, and international mobility committee. He collaborates with institutions in France, Germany, Belgium, and the UK on calixarene-based projects. Publications demonstrate expertise in calixarene derivatives, rotaxane/catenane synthesis, and nanomaterial functionalization. Over 2860 citations highlight impact in supramolecular and materials chemistry fields.

• Digital Humanities
• Bioinformatics
• Data Visualization
• +۵ مورد دیگر

Chris Tomlinson is a Research Fellow at Bibliotheca Hertziana (Max Planck Society), specializing in Digital Humanities. He holds a PhD in Parallel Computing and an MSc in Knowledge-Based Systems from the University of London. With over 25 years of experience as a Research Software Engineer, he has contributed to interdisciplinary projects spanning game theory, bioinformatics, and public health. Research Focus: His work integrates computational methods with humanities and life sciences, emphasizing: Development of analytical tools for biological and digital humanities research Data visualization and management systems for complex scientific datasets Image processing algorithms for biomedical applications Web-based platforms for collaborative research His publications demonstrate consistent innovation in computational tool development, with recent work focusing on computer vision for cell biology, metagenomics, and standardized data practices in systems biology. He maintains active involvement in academic training as a certified Software Carpentry instructor.

• Plant Genomics
• Structural Variation
• Pan-Genome Analysis
• +۷ مورد دیگر

Sara Pinosio is a Researcher at the Institute of Biosciences and BioResources (IBBR), part of the National Research Council of Italy (CNR), based in Florence. She holds a PhD in Agricultural Sciences and Biotechnology from the University of Udine and has extensive postdoctoral experience in plant genomics and bioinformatics. Her primary research interests include plant genomics , structural variation , pan-genome analysis , transcriptome and genome assembly , and the genetic effects of domestication . She applies advanced bioinformatics to study forest trees, crops, and non-model species. The analysis of her recent publications shows a strong focus on evolutionary genomics, particularly in forest trees (e.g., poplar, pine, coffee), with increasing attention to climate resilience and conservation. Her work spans from method development (e.g., genotyping technologies, transcriptome assembly) to large-scale comparative and population genomic studies. A notable recent trend is her interdisciplinary expansion into marine species (e.g., crabs) to study environmental stress responses. Ph.D. : Agricultural Sciences and Biotechnology, University of Udine (2012) Master’s : Medical Biotechnology, University of Udine (2008) Bachelor’s : Biotechnology (Computational Biology), University of Udine (2005) She has collaborated on numerous high-impact studies and is actively involved in generating genomic resources for conservation and breeding. Her work has significant implications for understanding plant evolution and improving resilience in the face of climate change.

• Forest Genetics
• Conservation Genetics
• Population Genetics
• +۷ مورد دیگر

Francesca Bagnoli is a Researcher at the Institute of Biosciences and BioResources (IBBR), part of the National Research Council of Italy (CNR) in Florence. She has been with IBBR since October 2014, following prior research roles at CNR's Institute of Plant Protection (IPSP) in Florence from 2011 to 2014. Her work is centered on forest genetics, conservation, and molecular marker applications. Education: Ph.D. in Agricultural and Forest Genetics, University of Florence (2002). Thesis: 'Isolation and molecular characterization of genes coding antioxidant enzymes in trees: Prunus persica and Pinus pinea'. Her research focuses on population and conservation genetics of forest trees, phylogeography, identification and use of molecular markers (SSRs, SNPs), and the molecular basis of adaptation in forest species using Bayesian statistical methods. She has contributed extensively to understanding the genetic diversity and evolutionary history of Mediterranean and European forest trees. Her recent publications (2021–2025) reveal strong trends in forest genomics, conservation planning, and climate adaptation. Key themes include latitudinal genetic diversity patterns in oaks, resilience of genetic diversity over geological timescales, spatial conservation planning for forest genetic resources, and microgeographical selection in conifers. Her work often integrates genomic data with ecological and paleoenvironmental evidence to infer demographic histories and adaptive processes. Scientific Projects and Collaborations: EU H2020 Forgenius: Improving access to forest genetic resources information. EU H2020 B4EST: Adaptive breeding for resilient forests under climate change. EU H2020 GenTree: Sustainable use of forest genetic resources in Europe. LIFE IP GESTIRE: Technical services for managing Lombard oak forests. Bilateral Italy-Montenegro projects on adaptive capacity of beech and pine along altitudinal gradients. Bagnoli has advised or collaborated with numerous researchers and institutions across Europe. While no formal students are listed, her role in large collaborative projects suggests significant mentorship and team leadership. She has contributed to major data platforms such as the GenTree Leaf and Dendroecological Collections, enhancing data accessibility for the scientific community. Laboratories and Research Teams: She is part of the Florence Division of IBBR-CNR, where she conducts research in forest molecular genetics and genomics. Her work is embedded within international consortia and EU-funded projects, involving close collaboration with INRAE (France), University of Florence, and other European research institutions. Her laboratory focuses on genetic analysis of forest tree populations using molecular markers and genomic tools.

Silvio C. E. Tosattoمشاهده پروفایل

استاد

• Bioinformatics
• Machine Learning
• Protein Structure
• +۵ مورد دیگر

Silvio C. E. Tosatto is a Full Professor of Bioinformatics at the Department of Biomedical Sciences, University of Padua (Italy), where he heads the BioComputing UP laboratory. He holds significant leadership roles within ELIXIR, the European infrastructure for life science data, serving as deputy Head of Node for ELIXIR Italy, member of the Data Platform Executive Committee, co-lead of the Cellular & Molecular Research priority area, and co-lead of the Machine Learning focus group. His research spans multiple areas of computational biology and bioinformatics with particular focus on protein structure analysis, machine learning applications in biology, cancer research, and personalized medicine. His work encompasses protein aggregation, repeat proteins, residue interaction networks, and infrastructure development for bioinformatics research. Analysis of his recent publications shows a strong emphasis on database development for protein science (Pfam, InterPro, RepeatsDB), integration of AI/ML approaches in biological data analysis, and applications in genetic variant interpretation for medical conditions like intellectual disability. His work demonstrates the convergence of traditional bioinformatics with modern machine learning techniques. Professor Tosatto maintains active research collaborations across Europe as evidenced by his extensive co-authorship networks. His leadership in ELIXIR highlights his significant contribution to European bioinformatics infrastructure development. He earned his PhD (Dr. rer. nat. with Magna cum laude distinction) in bioinformatics from Universität Mannheim in 2002, following a 1998 graduate degree in Computer Science & Business Administration from the same institution. He has been a Full Professor since October 2016. Fluent in English, Spanish, German, and Italian (native), Professor Tosatto operates effectively in international research environments and leads a productive research group focused on advancing computational approaches to biological problems.

Alexander Miguel Monzonمشاهده پروفایل

دانشیار

• Bioinformatics
• Structural Biology
• Protein Science
• +۴ مورد دیگر

Alexander Miguel Monzon is an Associate Professor in the Department of Information Engineering at the University of Padova, Italy, specializing in non-globular proteins including disordered and repetitive proteins. His work has significantly advanced bioinformatics through co-authorship of critical databases like DisProt, RepeatsDB, MobiDB, PED, and FuzDB, which represent the state-of-the-art in structural biology for non-globular proteins. Education: PhD in Basic and Applied Sciences (2018), National University of Quilmes, Argentina MSc in Bioinformatics (2012), National University of Entre Ríos, Argentina His research focuses on protein aggregation, structured tandem repeats, and intrinsic disorder. Recent work explores AI integration in protein research, conformational ensemble modeling, and sustainable computational methods. His publications span structural biology, database development, and machine learning applications. Monzon actively participates in international consortia including COST-action NGP-net, MSCA RISE IDPfun, REFRACT, H2020 Twinning PhasAGE, and serves as main proposer of the COST action ML4NGP. He has contributed to community standards for machine learning reporting in biology via the DOME Registry.