List of scientific works by Renato Umeton, Ph.D.
AI, Data Science, Machine Learning, Optimization, and Computer Science in Healthcare.
List of scientific works by Renato Umeton, Ph.D.
AI, Data Science, Machine Learning, Optimization, and Computer Science in Healthcare.
| Year | ||
| GPT-4 in a Cancer Center—Institute-Wide Deployment Challenges and Lessons Learned R Umeton, A Kwok, R Maurya, D Leco, N Lenane, J Willcox, GA Abel, et al. NEJM AI 1 (4), AIcs2300191, 2024 | 2024 | |
| Genomic and Immunophenotypic Landscape of Acquired Resistance to PD-(L) 1 Blockade in Non–Small-Cell Lung Cancer B Ricciuti, G Lamberti, SR Puchala, NR Mahadevan, JR Lin, JV Alessi, et al. Journal of Clinical Oncology, 23.00580, 2024 | 2 | 2024 |
| Book - Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part I G Nicosia, V Ojha, E La Malfa, G La Malfa, P Pardalos, R Umeton Book - Springer 14505 (http://dx.doi.org/10.1007/978-3-031-53969-5), 2024 | 2024 | |
| Book - Machine Learning, Optimization, and Data Science: 9th International Conference, LOD 2023, Grasmere, UK, September 22–26, 2023, Revised Selected Papers, Part II G Nicosia, V Ojha, E La Malfa, G La Malfa, P Pardalos, R Umeton Book - Springer 14506 (http://dx.doi.org/10.1007/978-3-031-53966-4), 2024 | 2024 | |
| Federated benchmarking of medical artificial intelligence with MedPerf A Karargyris, R Umeton, MJ Sheller, A Aristizabal, J George, A Wuest, et al. Nature Machine Intelligence 5, 799, 2023 | 38* | 2023 |
| A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories D Placido, B Yuan, JX Hjaltelin, C Zheng, AD Haue, PJ Chmura, C Yuan, et al. Nature Medicine 29, 1113, 2023 | 53 | 2023 |
| GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows S Pati, SP Thakur, İE Hamamcı, U Baid, B Baheti, M Bhalerao, O Güley, et al. Communications Engineering 2, 23, 2023 | 41 | 2023 |
| Measuring Palliative Care Communication via Telehealth: A Pilot Study EC Tarbi, BN Durieux, JM Brain, A Kwok, R Umeton, S Samineni, et al. Journal of Pain and Symptom Management 66, E155, 2023 | 1 | 2023 |
| PI‐RADS 3 score: A retrospective experience of clinically significant prostate cancer detection A Camacho, F Salah, CP Bay, J Waring, R Umeton, MS Hirsch, AP Cole, et al. BJUI Compass 4, 473, 2023 | 2023 | |
| Book - Machine Learning, Optimization, and Data Science: 8th International Workshop, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers, Part I G Nicosia, V Ojha, E La Malfa, G La Malfa, P Pardalos, G Di Fatta, et al. Book - Springer 13810 (http://dx.doi.org/10.1007/978-3-031-25599-1), 2023 | 1* | 2023 |
| Book - Machine Learning, Optimization, and Data Science: 8th International Workshop, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers, Part II G Nicosia, V Ojha, E La Malfa, G La Malfa, P Pardalos, G Di Fatta, et al. Book - Springer 13811 (http://dx.doi.org/10.1007/978-3-031-25891-6), 2023 | 2023 | |
| Spatially aware deep learning reveals tumor heterogeneity patterns that encode distinct kidney cancer states J Nyman, T Denize, Z Bakouny, C Labaki, BM Titchen, K Bi, SN Hari, et al. Cell Reports Medicine 4 (9), 2023 | 2 | 2023 |
| PDF - Federated Learning Framework for NLP in Healthcare: Assessing Hospital Readmission Using Electronic Health Records S Nalawade, S Samineni, A Chowdhury, L Feng, R Umeton, M Rosenthal Bio-IT World (dx.doi.org/10.6084/m9.figshare.23269184.v2), 2023 | 2023 | |
| Circulating U13 Small Nucleolar RNA as a Potential Biomarker in Huntington’s Disease: A Pilot Study S Romano, C Romano, M Peconi, A Fiore, G Bellucci, E Morena, F Troili, et al. International Journal of Molecular Sciences 23 (20), 12440, 2022 | 2 | 2022 |
| Multi-omics biomarkers aid prostate cancer prognostication Z Xu, M Omar, E Benedetti, J Rosenthal, R Umeton, J Krumsiek, et al. bioRxiv, 2022.09. 20.508244, 2022 | 1 | 2022 |
| Book Chapter - A Review of Medical Federated Learning: Applications in Oncology and Cancer Research A Chowdhury, H Kassem, N Padoy, R Umeton, A Karargyris Book Chapter MICCAI - Springer 1 (dx.doi.org/10.6084/m9.figshare.21071200), 3-24, 2022 | 35* | 2022 |
| GWAS Variants, Non-genetic Factors, and Transient Transcriptome in Multiple Sclerosis Etiopathogenesis R Umeton, G Bellucci, R Bigi, R Mechelli, V Rinaldi, M Buscarinu, et al. EUROPEAN JOURNAL OF NEUROLOGY 29, 456-457, 2022 | 2022 | |
| Association of High Tumor Mutation Burden in Non–Small Cell Lung Cancers With Increased Immune Infiltration and Improved Clinical Outcomes of PD-L1 Blockade Across PD-L1 … B Ricciuti, X Wang, JV Alessi, H Rizvi, NR Mahadevan, YY Li, A Polio, et al. JAMA Oncology, doi:10.1001/jamaoncol.2022.1981, 2022 | 136 | 2022 |
| A multi-omics signature for patients’ risk classification in prostate cancer Z Xu, E Benedetti, R Carelli, J Rosenthal, H Pakula, M Omar, R Umeton, et al. Cancer Research 82 (12), 5858, 2022 | 2022 | |
| Associations between family member involvement and outcomes of patients admitted to the intensive care unit: retrospective cohort study TF Gray, A Kwok, KM Do, S Zeng, ET Moseley, YM Dbeis, R Umeton, et al. JMIR Medical Informatics 10 (6), e33921, 2022 | 1 | 2022 |
| Using attention-based deep multiple instance learning to identify key genetic alterations in prostate cancer from whole slide images M Omar, Z Xu, R Carelli, J Rosenthal, D Brundage, DC Salles, EL Imada, et al. Cancer Research 82 (12), 462, 2022 | 2022 | |
| AI predicts risk of pancreatic cancer from disease trajectories using real-world electronic health records (EHRs) from Denmark and the USA D Placido, B Yuan, JX Hjaltelin, AD Haue, PJ Chmura, C Yuan, J Kim, et al. Cancer Research 82 (12), LB550, 2022 | 2022 | |
| Deep learning for cancer symptoms monitoring on the basis of electronic health record unstructured clinical notes C Lindvall, CY Deng, ND Agaronnik, A Kwok, S Samineni, R Umeton, et al. JCO Clinical Cancer Informatics 6, e2100136, 2022 | 12 | 2022 |
| Multiple sclerosis genetic and non-genetic factors interact through the transient transcriptome R Umeton, G Bellucci, R Bigi, S Romano, MC Buscarinu, R Reniè, et al. Scientific reports 12 (1), 7536, 2022 | 6 | 2022 |
| Circulating U13 small nucleolar RNA as a candidate biomarker for Huntington’s disease S Romano, C Romano, M Peconi, A Fiore, G Bellucci, E Morena, F Troili, et al. bioRxiv, 2022.04. 22.489178, 2022 | 2022 | |
| Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology J Rosenthal, R Carelli, M Omar, D Brundage, E Halbert, J Nyman, SN Hari, et al. Molecular Cancer Research 21 (655), 2022 | 27 | 2022 |
| Machine Learning, Optimization, and Data Science: Part II G Nicosia, V Ojha, EL Malfa, GL Malfa, G Jansen, P Pardalos, G Giuffrida, et al. Lecture Notes in Computer Science, 2022 | 2022 | |
| Book - Machine Learning, Optimization, and Data Science: 7th International Conference, LOD 2021, Grasmere, UK, October 4-8, 2021, Revised Selected Papers, Part I G Nicosia, V Ojha, E La Malfa, G La Malfa, G Jansen, PM Pardalos, et al. Book - Springer 13163 (http://doi.org/10.1007/978-3-030-95467-3), 1-644, 2022 | 2022 | |
| Book - Machine Learning, Optimization, and Data Science: 7th International Conference, LOD 2021, Grasmere, UK, October 4-8, 2021, Revised Selected Papers, Part II G Nicosia, V Ojha, E La Malfa, G La Malfa, G Jansen, PM Pardalos, et al. Book - Springer 13164 (http://doi.org/10.1007/978-3-030-95470-3), 1-548, 2022 | 2022 | |
| Identification and Management of Pathogenic Variants in BRCA1, BRCA2, and PALB2 in a Tumor-Only Genomic Testing Program BL Bychkovsky, T Li, J Sotelo, N Tayob, J Mercado, I Gomy, A Chittenden, et al. Clinical cancer research: an official journal of the American Association …, 2022 | 9 | 2022 |
| Whole Slide Image to DICOM Conversion as Event-Driven Cloud Infrastructure D Brundage, J Rosenthal, R Carelli, S Rand, R Umeton, M Loda, et al. arXiv preprint arXiv:2203.13888, 2022 | 2022 | |
| Examining Batch Effect in Histopathology as a Distributionally Robust Optimization Problem SN Hari, J Nyman, N Mehta, H Elmarakeby, B Jiang, F Dietlein, et al. bioRxiv, 2021.09. 14.460365, 2021 | 1 | 2021 |
| Applying Self-Supervised Learning to Medicine: Review of the State of the Art and Medical Implementations A Chowdhury, J Rosenthal, J Waring, R Umeton Informatics 8 (3, Machine Learning in Healthcare), 59, 2021 | 55 | 2021 |
| Pancreatic cancer risk predicted from disease trajectories using deep learning D Placido, B Yuan, JX Hu, AD Haue, C Yuan, J Kim, R Umeton, G Antell, et al. bioRxiv, 2021 | 13 | 2021 |
| Metabolomics of Prostate Cancer Gleason Score in Tumor Tissue and Serum KL Penney, S Tyekucheva, J Rosenthal, H El Fandy, R Carelli, et al. Molecular Cancer Research [machine learning; metabolomics; prostate cancer …, 2021 | 26 | 2021 |
| Enrichment analysis of GWAS data in autoimmunity delineates the multiple sclerosis-Epstein Barr virus association R Mechelli, R Umeton, V Rinaldi, G Bellucci, R Bigi, DF Angelini, et al. BioRxiv, 2021.06. 06.447253, 2021 | 2021 | |
| Identification and management of pathogenic mutations in BRCA1, BRCA2, and PALB2 in a tumor-only genomic testing program. BL Bychkovsky, T Li, J Sotelo, N Tayob, J Mercado, I Gomy, et al. Journal of Clinical Oncology 39 (15_suppl), 10528-10528, 2021 | 1 | 2021 |
| GWAS-associated Variants, Non-genetic Factors and Transient Transcriptome in Multiple Sclerosis Etiopathogenesis: a Colocalization Analysis R Umeton, G Bellucci, R Bigi, S Romano, MC Buscarinu, R Reniè, et al. bioRxiv, 2021.03. 12.434773, 2021 | 2021 | |
| Book - Machine Learning, Optimization, and Data Science (6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part I) G Nicosia, V Ojha, L Malfa E., G Jansen, V Sciacca, P Pardalos, et al. Book - Springer 12565 (http://doi.org/10.1007/978-3-030-64583-0), 1-740, 2021 | 1* | 2021 |
| Book - Machine Learning, Optimization, and Data Science (6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II) G Nicosia, V Ojha, L Malfa E., G Jansen, V Sciacca, P Pardalos, et al. Book - Springer 12566 (http://doi.org/10.1007/978-3-030-64580-9), 1-666, 2021 | 2021 | |
| Triple-negative breast cancer M Huang, J O'Shaughnessy, J Zhao, A Haiderali, J Cortés, SD Ramsey, et al. | 4 | 2021 |
| Using Distributionally Robust Optimization to improve robustness in cancer pathology SN Hari, E Van Allen, J Nyman, N Mehta, B Jiang, H Elmarakeby, et al. NeurIPS 2021 Workshop on Distribution Shifts: Connecting Methods and …, 2021 | 2021 | |
| Building tools for machine learning and artificial intelligence in cancer research: best practices and a case study with the PathML toolkit for computational pathology J Rosenthal, R Carelli, M Omar, D Brundage, E Halbert, J Nyman, SN Hari, et al. biorxiv, 10.1101/2021.10.21.46521, 2021 | 2021 | |
| GWAS-associated variants, non-genetic factors, and transient transcriptome in multiple sclerosis etiopathogenesis: A colocalization analysis G Bellucci, R Umeton, R Bigi, S Romano, MC Buscarinu, R Reniè, et al. Journal of the Neurological Sciences 429, 2021 | 2021 | |
| Associations Between Family Member Involvement and Outcomes of Patients Admitted to the Intensive Care Unit: Retrospective Cohort Study T Fowler Gray, A Kwok, KM Do, S Zeng, ET Moseley, YM Dbeis, et al. Journal of Medical Internet Research, 33921, 2021 | 2021 | |
| A very high tumor mutational burden (TMB) is associated with improved efficacy of PD-(L) 1 inhibition across different PD-L1 expression subgroups and a distinct immunophenotype … B Ricciuti, KC Arbour, NR Mahadevan, JV Alessi, J Lindsay, R Umeton, et al. Cancer Research 81 (13), 490, 2021 | 2021 | |
| Circulating hsa-miR-323b-3p in Huntington's Disease: A Pilot Study M Ferraldeschi, S Romano, S Giglio, C Romano, E Morena, R Mechelli, et al. Frontiers in neurology 12, 492, 2021 | 10 | 2021 |
| Book - Machine Learning, Optimization, and Data Science (5th International Conference, LOD 2019, Siena, Italy, September 10–13, 2019, Proceedings) G Nicosia, P Pardalos, R Umeton, G Giuffrida, V Sciacca Book - Springer 11943 (http://doi.org/10.1007/978-3-030-37599-7), 1-772, 2020 | 1* | 2020 |
| Automated Machine Learning: Review of the State-of-the-Art and Opportunities for Healthcare J Waring, C Lindvall, R Umeton Artificial Intelligence in Medicine, 101822, 2020 | 604 | 2020 |
| 246 Clinicopathologic and genomic correlates of tumor mutational burden and its impact on PD-(L) 1 inhibition efficacy in non-small cell lung cancer according to different PD … B Ricciuti, N Mahadevan, R Umeton, J Alessi, A Polio, N Vokes, et al. Journal for ImmunoTherapy of Cancer 8 (Suppl 3), 2020 | 1 | 2020 |
| Clinical pan-cancer assessment of mismatch repair deficiency using tumor-only, targeted next-generation sequencing A Albayrak, AC Garrido-Castro, M Giannakis, R Umeton, MD Manam, et al. JCO Precision Oncology 4, 1084-1097, 2020 | 12 | 2020 |
| Genomic correlates of PD-L1 expression are associated with response to immunotherapy in non-small cell lung cancer LF Spurr, G Lamberti, YY Li, B Ricciuti, G Recondo, R Umeton, LM Sholl, et al. Cancer Research 80 (16), 5668, 2020 | 2020 | |
| Impact of DNA damage response and repair (DDR) gene mutations on efficacy of PD-(L) 1 immune checkpoint inhibition in non–small cell lung cancer B Ricciuti, G Recondo, LF Spurr, YY Li, G Lamberti, D Venkatraman, et al. Clinical cancer research 26 (15), 4135-4142, 2020 | 110 | 2020 |
| Clinicopathological and genomic correlates of programmed cell death ligand 1 (PD-L1) expression in nonsquamous non-small-cell lung cancer G Lamberti, LF Spurr, Y Li, B Ricciuti, G Recondo, R Umeton, M Nishino, et al. Annals of Oncology 31 (6), 807-814, 2020 | 84 | 2020 |
| Molecular Mechanisms of Acquired Resistance to MET Tyrosine Kinase Inhibitors in Patients with MET Exon 14–Mutant NSCLC G Recondo, M Bahcall, LF Spurr, J Che, B Ricciuti, GC Leonardi, YC Lo, et al. Clinical Cancer Research 26 (11), 2615, 2020 | 142 | 2020 |
| Tumor mutational burden and PTEN alterations as molecular correlates of response to PD-1/L1 blockade in metastatic triple-negative breast cancer R Barroso-Sousa, TE Keenan, S Pernas, P Exman, E Jain, et al. Clinical Cancer Research 26 (11), 2565, 2020 | 142 | 2020 |
| Reworking GWAS data to understand the role of nongenetic factors in MS etiopathogenesis R Mechelli, R Umeton, G Manfrè, S Romano, MC Buscarinu, V Rinaldi, et al. Genes 11 (1), 97, 2020 | 5 | 2020 |
| Correction to: Machine Learning, Optimization, and Data Science G Nicosia, V Ojha, E La Malfa, G Jansen, V Sciacca, P Pardalos, et al. Machine Learning, Optimization, and Data Science: 6th International …, 2020 | 2020 | |
| PDF - Operationalizing Artificial Intelligence: Lessons Learned at Dana-Farber Cancer Institute J Methot, G Antell, R Umeton AMIA 2020 (dx.doi.org/10.6084/m9.figshare.22186741), 1-2, 2020 | 2020 | |
| Machine Learning, Optimization, and Data Science G Nicosia, V Ojha, E La Malfa, G Jansen, V Sciacca, P Pardalos, et al. Springer Nature, 2020 | 2020 | |
| Book - Machine Learning, Optimization, and Data Science (4th International Conference, LOD 2018, Volterra, Italy, September 13-16, 2018, Revised Selected Papers) G Nicosia, P Pardalos, G Giuffrida, R Umeton, V Sciacca Book - Springer 11331 (http://doi.org/10.1007/978-3-030-13709-0), 1-584, 2019 | 1* | 2019 |
| Clinicopathological and genomic correlates of PD-L1 expression in nonsquamous non-small cell lung cancer G Lamberti, L Spurr, Y Li, B Ricciuti, G Recondo, R Umeton, A Cherniak, et al. Journal for Immunotherapy of Cancer 7, 2019 | 1 | 2019 |
| Use of targeted next generation sequencing to characterize tumor mutational burden and efficacy of immune checkpoint inhibition in small cell lung cancer B Ricciuti, S Kravets, SE Dahlberg, R Umeton, A Albayrak, SJ Subegdjo, et al. Journal for ImmunoTherapy of Cancer 7 (1), 87, 2019 | 76 | 2019 |
| Harmonization of tumor mutational burden quantification and association with response to immune checkpoint blockade in non–small-cell lung cancer NI Vokes, D Liu, B Ricciuti, E Jimenez-Aguilar, H Rizvi, F Dietlein, MX He, et al. JCO precision oncology 3, 1-12, 2019 | 100 | 2019 |
| Comparison of Clinicopathological and Genomic Characteristics Between NSCLCs with a PD-L1 Tumor Proportion Score of≥ 90% vs< 1% G Lamberti, Y Li, L Spurr, B Ricciuti, G Recondo, R Umeton, L Sholl, et al. Journal of Thoracic Oncology 14 (10), S720, 2019 | 2 | 2019 |
| Mechanisms of Resistance to MET Tyrosine Kinase Inhibitors in Patients with MET Exon 14 Mutant Non-Small Cell Lung Cancer G Recondo, M Bahcall, L Sholl, G Leonardi, B Ricciuti, T Nguyen, et al. Journal of Thoracic Oncology 14 (10), S285, 2019 | 4 | 2019 |
| DNA Damage Response Gene Alterations Are Associated with High Tumor Mutational Burden and Clinical Benefit from PD-1 Axis Inhibition in NSCLC B Ricciuti, M Cheng, G Recondo, R Umeton, M Nishino, L Sholl, M Awad Journal of Thoracic Oncology 14 (10), S439, 2019 | 2 | 2019 |
| Immune-Related Adverse Events and Clinical Outcome to Anti PD-1 Axis Inhibition in SCLC: A Multicenter Retrospective Analysis B Ricciuti, AR Naqash, B Henick, D Rangachari, J Naidoo, et al. Journal of Thoracic Oncology 14 (10), S213, 2019 | 3 | 2019 |
| Tumor mutational burden (TMB) is a potential predictor of response to immune checkpoint inhibitors (ICI) in metastatic triple-negative breast cancer (mTNBC) R Barroso-Sousa, S Tyekucheva, P Exman, R Umeton, FS Hodi, EP Winer, et al. Mastology 29 (3), 5-5, 2019 | 2019 | |
| Inter-test variability in tumor mutational burden (TMB) quantification and identification of TMB thresholds N Vokes, EJ Alguilar, R Umeton, A Adeni, L Sholl, M Hellmann, H Rizvi, et al. Cancer Research 79 (13), 2514, 2019 | 1 | 2019 |
| Impact of KRAS allele subtypes and concurrent genomic alterations on clinical outcomes to programmed death 1 axis blockade in non-small cell lung cancer. B Ricciuti, G Recondo, R Umeton, M Nishino, LM Sholl, MM Awad Journal of Clinical Oncology 37, 9082, 2019 | 5 | 2019 |
| DNA damage response gene alterations are associated with high tumor mutational burden and clinical benefit from programmed death 1 axis inhibition in non-small cell lung cancer. B Ricciuti, ML Cheng, G Recondo, M Nishino, R Umeton, LM Sholl, et al. Journal of Clinical Oncology 37, 9077, 2019 | 3 | 2019 |
| Significant enrichment of Herpesvirus interactors in GWAS data suggests causal inferences for the association between Epstein Barr virus and multiple sclerosis R Mechelli, R Umeton, S Srinivasan, A Fornasiero, M Ferraldeschi, et al. bioRxiv, 624049, 2019 | 2019 | |
| Mutational analysis of 472 urothelial carcinoma across grades and anatomic sites AH Nassar, R Umeton, J Kim, K Lundgren, L Harshman, EM Van Allen, et al. Clinical Cancer Research 25 (8), 2458, 2019 | 109 | 2019 |
| PTEN alterations and tumor mutational burden as potential predictors of resistance or response to immune checkpoint inhibitors in metastatic triple-negative breast cancer R Barroso-Sousa, S Tyekucheva, S Pernas-Simon, P Exman, E Jain, et al. Cancer Research 79, P5, 2019 | 1* | 2019 |
| Genome-Wide Multiple Sclerosis Association Data and Coagulation S La Starza, M Ferraldeschi, MC Buscarinu, S Romano, A Fornasiero, et al. Frontiers in Neurology 10, 95, 2019 | 10 | 2019 |
| Book - Machine Learning, Optimization, and Big Data (Third International Conference, MOD 2017, Volterra, Italy, September 14–17, 2017, Revised Selected Papers) G Nicosia, P Pardalos, G Giuffrida, R Umeton Book - Springer 10710 (http://doi.org/10.1007/978-3-319-72926-8), 1-621, 2018 | 1* | 2018 |
| Use of Tumor-Only Next Generation Sequencing to Identify Clinicopathologic and Genomic Correlates of Tumor Mutational Burden and Immunotherapy Response in Non-Small Cell Lung … M Awad, NR Mahadevan, A Polio, EJ Aguilar, NI Vokes, B Ricciuti, et al. Preprints with The Lancet, 2018 | 2018 | |
| Investigating the gene-environment interaction in multiple sclerosis through a" candidate-interactome" approach G Pellicciari, R Umeton, S Srinivasan, R Magliozzi, F Cinthia, C Romano, et al. MULTIPLE SCLEROSIS JOURNAL 24, 192-193, 2018 | 2018 | |
| Multiple sclerosis: Epstein-Barr virus variants' role to understand the etiology E Morena, R Renie, C Romano, G Pellicciari, G Pesole, G Manfre, et al. MULTIPLE SCLEROSIS JOURNAL 24, 397-398, 2018 | 2018 | |
| Efficacy and Genomic Correlates of Response to Anti-PD1/PD-L1 Blockade in Non-Small Cell Lung Cancers Harboring Targetable Oncogenes N Vokes, EJ Alguilar, A Adeni, R Umeton, L Sholl, H Rizvi, M Hellmann, et al. Journal of Thoracic Oncology 13 (10), S422, 2018 | 9 | 2018 |
| PD-L1 Expression, Tumor Mutational Burden, and Response to Immunotherapy in Patients with MET exon 14 Altered Lung Cancers JK Sabari, GC Leonardi, CA Shu, R Umeton, J Montecalvo, A Ni, R Chen, et al. Annals of Oncology, 2018 | 253 | 2018 |
| Comprehensive genomic characterization of urothelial carcinomas A Nassar, R Umeton, K Lundgren, LC Harshman, EM Van Allen, et al. Journal of Clinical Oncology 36 (15), 4527, 2018 | 2018 | |
| Optimization and Data Science G Nicosia, P Pardalos, G Giuffrida, R Umeton, V Sciacca | 2018 | |
| Mismatch repair deficiency in high-grade meningioma: a rare but recurrent event associated with dramatic immune activation and clinical response to PD-1 blockade IF Dunn, Z Du, M Touat, MB Sisti, PY Wen, R Umeton, AM Dubuc, et al. JCO precision oncology 2, 2018 | 48 | 2018 |
| Fractal analysis of retinal vascular morphology in multiple sclerosis M Cavallari, D Kimbrough, C Stamile, R Umeton, T Chitnis, C Guttmann MULTIPLE SCLEROSIS JOURNAL 24, 370, 2018 | 1 | 2018 |
| Analysis of coding and non-coding transcriptome of peripheral B cells reveals an altered interferon response factor (IRF)-1 pathway in multiple sclerosis patients V Annibali, R Umeton, A Palermo, M Severa, MP Etna, S Giglio, et al. Journal of NeuroImmunology 324, 165, 2018 | 10 | 2018 |
| Intestinal Permeability in Relapsing-Remitting Multiple Sclerosis MC Buscarinu, S Romano, R Mechelli, RP Umeton, M Ferraldeschi, et al. Neurotherapeutics, 1-7, 2018 | 71 | 2018 |
| Somatic mutations in CDH1 and CTNNB1 in primary carcinomas at 13 anatomic sites EL Busch, JL Hornick, R Umeton, A Albayrak, NI Lindeman, et al. Oncotarget 8 (49), 85680, 2017 | 18 | 2017 |
| Different environmental stimuli may activate common biological processes potentially involved in multiple sclerosis R Mechelli, R Umeton, R Renie, G Ristori, M Salvetti MULTIPLE SCLEROSIS JOURNAL 23, 210, 2017 | 2017 | |
| The gut microbiome in active and stable relapsing multiple sclerosis E Eleftheriou, RP Umeton, R Umeton, S Nedelcu, AL Contreras, L Hall, et al. MULTIPLE SCLEROSIS JOURNAL 23, 518, 2017 | 2017 | |
| A staged screening of registered drugs highlights remyelinating drug candidates for clinical trials C Eleuteri, S Olla, C Veroni, R Umeton, R Mechelli, S Romano, et al. Scientific Reports 7, 45780, 2017 | 36 | 2017 |
| Altered intestinal permeability in patients with relapsing–remitting multiple sclerosis: A pilot study MC Buscarinu, B Cerasoli, V Annibali, C Policano, L Lionetto, M Capi, et al. Multiple Sclerosis Journal 23 (3), 442-446, 2017 | 146 | 2017 |
| Association of Rs7961894 with Mean Platelet Volume in Patients with Acute Ischemic Stroke M Miller, N Henninger, R Umeton, A Slowik Stroke 48, ATP202, 2017 | 2017 | |
| Gene-environment interaction study in multiple sclerosis using a" candidate-interactome" approach R Mechelli, R Umeton, Imsgc-Wtccc, G Ristori, M Salvetti MULTIPLE SCLEROSIS JOURNAL 22, 191-192, 2016 | 2016 | |
| GENE-ENVIRONMENT INTERACTION STUDY IN MULTIPLE SCLEROSIS R Mechelli, R Umeton, I WTCCC22, G Ristori, M Salvetti | 2016 | |
| Epstein barr virus genotipic variants and uses thereof as risk predictors, biomarkers and therapeutic targets in multiple sclerosis G Ristori, R Mechelli, M Salvetti, C Policano, R Umeton US Patent App. 14/782,556, 2016 | 2016 | |
| Portable medical device and method for quantitative retinal image analysis through a smartphone C Stamile, R Umeton, M Cavallari, F Calimeri, F Orzi US Patent 20150320313A1, 2016 | 1 | 2016 |
| Novel method for automated analysis of retinal images: results in subjects with hypertensive retinopathy and CADASIL M Cavallari, C Stamile, R Umeton, F Calimeri, F Orzi BioMed research international 2015, 2015 | 42 | 2015 |
| IFN-β and multiple sclerosis: from etiology to therapy and back V Annibali, R Mechelli, S Romano, MC Buscarinu, A Fornasiero, et al. Cytokine & growth factor reviews 26 (2), 221-228, 2015 | 50 | 2015 |
| Research Article Novel Method for Automated Analysis of Retinal Images: Results in Subjects with Hypertensive Retinopathy and CADASIL M Cavallari, C Stamile, R Umeton, F Calimeri, F Orzi | 2015 | |
| Epstein-Barr virus genetic variants are associated with multiple sclerosis. R Mechelli, C Manzari, C Policano, A Annese, E Picardi, R Umeton, et al. Neurology 31 (84), 1362-8, 2015 | 67 | 2015 |
| B cell IRF1 pathway is dysregulated in multiple sclerosis V Annibali, R Umeton, A Palermo, MC Buscarinu, C Policano, R Mechelli, et al. Journal of Neuroimmunology 275 (1), 1, 2014 | 2014 | |
| Noise in multiple sclerosis: unwanted and necessary I Bordi, VAG Ricigliano, R Umeton, G Ristori, F Grassi, A Crisanti, et al. Annals of Clinical and Translational Neurology 1 (7), 502-511, 2014 | 9 | 2014 |
| Dispositivo medico portatile e metodo per l’acqusizione di immagini della retina e esecuzione di analisi quantitative sull’immagi-ne della retina C Stamile, R Umeton, M Cavallari, F Calimeri, F Orzi | 2014 | |
| Drug repositioning and computational analysis for myelin disease regenerative therapies C Eleuteri, C Veroni, M Floris, S Olla, R Umeton, G Ristori, V Annibali, et al. MULTIPLE SCLEROSIS JOURNAL 19 (11), 163-163, 2013 | 2013 | |
| A mechanistic, stochastic model helps understand multiple sclerosis course and pathogenesis I Bordi, R Umeton, VAG Ricigliano, V Annibali, R Mechelli, G Ristori, et al. International Journal of Genomics 2013, 2013 | 29 | 2013 |
| Contribution of genome-wide association studies to scientific research: a pragmatic approach to evaluate their impact VAG Ricigliano, R Umeton, L Germinario, E Alma, M Briani, N Di Segni, et al. PLoS One 8 (8), e71198, 2013 | 9 | 2013 |
| In silico modeling of shear-stress-induced nitric oxide production in endothelial cells through systems biology A Koo, D Nordsletten, R Umeton, et al. Biophysical journal 104 (10), 2295-2306, 2013 | 50 | 2013 |
| Efficient behavior of photosynthetic organelles via Pareto optimality, identifiability, and sensitivity analysis G Carapezza, R Umeton, J Costanza, C Angione, G Stracquadanio, et al. ACS synthetic biology 2 (5), 274-288, 2013 | 13 | 2013 |
| A “candidate-interactome” aggregate analysis of genome-wide association data in multiple sclerosis R Mechelli, R Umeton, C Policano, V Annibali, G Coarelli, VAG Ricigliano, et al. PLoS One 8 (5), e63300, 2013 | 36 | 2013 |
| Automated analysis of retinal photographs: results in subjects with hypertensive retinopathy and CADASIL M Cavallari, C Stamile, R Umeton, F Orzi NEUROLOGY 80, 2013 | 1 | 2013 |
| Automated Analysis of Retinal Photographs: Results in Subjects with Hypertensive Retinopathy and CADASIL (P06. 009) M Cavallari, C Stamile, R Umeton, F Orzi Neurology 80 (7 Supplement), P06. 009-P06. 009, 2013 | 2013 | |
| Research Article A Mechanistic, Stochastic Model Helps Understand Multiple Sclerosis Course and Pathogenesis I Bordi, R Umeton, VAG Ricigliano, V Annibali, R Mechelli, G Ristori, et al. | 2013 | |
| Varianti genotipiche del virus di Epstein Barr e loro usi come possibili predittori di rischio, biomarcatori e target terapeutici nella sclerosi multipla R Mechelli, C Policano, R Umeton, M Salvetti, G Ristori ITA, 2013 | 2013 | |
| A ‘‘Candidate-Interactome’’Aggregate Analysis of Genome-Wide Association Data R Mechelli, R Umeton, C Policano, V Annibali, G Coarelli | 2013 | |
| OREMPdb: a semantic dictionary of computational pathway models R Umeton, G Nicosia, CF Dewey BMC bioinformatics 13, 1-9, 2012 | 8 | 2012 |
| Methylation-dependent PAD2 upregulation in multiple sclerosis peripheral blood R Calabrese, M Zampieri, R Mechelli, V Annibali, T Guastafierro, et al. Multiple Sclerosis Journal 18 (3), 299-304, 2012 | 86 | 2012 |
| Characterization of Epstein-Barr virus genotypes in multiple sclerosis by 454 deep sequencing C Manzari, E Picardi, R Mechelli, C Policano, R Umeton, A Paluscio, et al. 2012 Human Microbiome International Conference–Paris, France, March 19-21 2012, 2012 | 2012 | |
| Characterization of Epstein-Barr virus genotypes in multiple sclerosis C Policano, R Mechelli, C Manzari, E Picardi, V Annibali, R Umeton, et al. -, 2012 | 2012 | |
| metaDesign: Bacterial Strain Design Automation Software C Jole, C Giovanni, A Claudio, U Renato, L Pietro, G Nicosia IWBDA 2012, 2012 | 2012 | |
| Efficient Behavior of Photosynthetic Organelles via Pareto Optimality, Identifiability and Sensitivity Analysis-Appendix Supplementary Information G Carapezza, R Umeton, J Costanza, C Angione, G Stracquadanio, et al. | 2012 | |
| Modeling and Optimization of Efficient Photosynthetic Organelles-Appendix Supplementary Information G Carapezza, R Umeton, J Costanza, C Angione, G Stracquadanio, et al. | 2012 | |
| New enhancers of endogenous remyelination: an extensive in vitro and ex vivo screening C Eleuteri, C Veroni, R Umeton, V Annibali, G Ristori, M Salvetti, C Agresti MULTIPLE SCLEROSIS, 2012 | 2 | 2012 |
| Transciptome of B lymphocytes in multiple sclerosis V Annibali, R Umeton, A Annese, A Palermo, R Mechelli, C Policano, et al. JOURNAL OF NEUROIMMUNOLOGY 253, 9-9, 2012 | 2012 | |
| Identification of sensitive enzymes in the photosynthetic carbon metabolism R Umeton, G Stracquadanio, A Papini, J Costanza, P Lio, G Nicosia Advances in Systems Biology, 441-459, 2012 | 5 | 2012 |
| Design of robust metabolic pathways R Umeton, G Stracquadanio, A Sorathiya, P Liò, A Papini, G Nicosia Proceedings of the 48th Design Automation Conference, 747-752, 2011 | 16 | 2011 |
| Design and implementation of a workflow-based system for the analysis of HumanExon and microRNA array chip data A Palermo, V Annibali, A Annese, G Ristori, M Salvetti, F Calimeri, et al. ICARIS, 2011 | 2011 | |
| OREMPdb: a Semantic Dictionary of Runnable Biological Circuits R Umeton, G Nicosia, CF Dewey Jr BITS, 2011 | 2011 | |
| Semantic Queries for Biomedical Pathways R Umeton, G Nicosia, CF Dewey Jr 10th Workshop on Process Algebra and Stochastically Timed Activities (PASTA …, 2011 | 2011 | |
| Multi-scale Mathematical Modeling to Support Drug Development DA Nordsletten, BY Yankama, R Umeton, et al. IEEE Transactions on Biomedical Engineering, 2011 | 16 | 2011 |
| Large scale agent-based modeling of the humoral and cellular immune response G Stracquadanio, R Umeton, J Costanza, V Annibali, R Mechelli, et al. International Conference on Artificial Immune Systems (ICARIS 2011), 15-29, 2011 | 3 | 2011 |
| Optimization and Ontology for Computational Systems Biology R Umeton | 2010 | |
| Analysis and optimization of c3 photosynthetic carbon metabolism G Stracquadanio, R Umeton, A Papini, P Lio, G Nicosia 2010 IEEE International Conference on BioInformatics and BioEngineering, 44-51, 2010 | 21 | 2010 |
| A Cross-Format Framework for Consistent Information Integration among Molecular Pathways and Ontologies R Umeton, B Yankama, G Nicosia, CF Dewey 6th World Congress of Biomechanics (WCB 2010). August 1-6, 2010 Singapore …, 2010 | 3 | 2010 |
| Key Enzymes for the optimization of CO2 uptake and nitrogen consumption in the C3 photosynthetic carbon metabolism A Papini, G Nicosia, G Stracquadanio, P Lio, R Umeton Journal of Biotechnology, 525, 2010 | 3 | 2010 |
| OREMP: Ontology Reasoning Engine for Molecular Pathways R Umeton, B Yankama, G Nicosia, CF Dewey Jr 1st International Workshop on Ontology Repositories and Editors for the …, 2010 | 2 | 2010 |
| Visita Massachusetts Institute of Technology (MIT) R Umeton, M Salvetti USA, 2009 | 2009 | |
| Highway traffic simulator based on cellular automata model: preliminary results and congestion pricing analysis S DI GREGORIO, R Umeton, A Bicocchi, A Evangelisti, MA Gonzales 20TH European Modeling & Simulation Symposium (EMSS), 665-674, 2008 | 1 | 2008 |
| Highway traffic model based on cellular automata: Preliminary simulation results with congestion pricing considerations S Di Gregorio, R Umeton, A Bicocchi, A Evangelisti, MC Gonzalez 20th European Modeling and Simulation Symposium, EMSS 2008, 17-19 September …, 2008 | 3 | 2008 |
| A Cellular Automata Model for Highway Traffic with Preliminary Results S Di Gregorio, R Umeton, A Bicocchi, A Evangelisti Artificial Life and Evolutionary Computation: Proceedings of Wivace 2008, 235, 2008 | 1 | 2008 |
| Admissible Method for Improved Genetic Search in Cellular Automata Model Hyperparameter Space (AMMISCA): a Strategy in Genetic Calibration with Preliminary Results R Umeton, S Di Gregorio Artificial Life and Evolutionary Computation: Proceedings of Wivace 2008, 99, 2008 | 1* | 2008 |
| Introduction of More Physical Features in the Cellular Automata Model for Lava Flows SCIARA: Preliminary Results Regarding the Viscosity MV Avolio, GM Crisci, S Di Gregorio, R Rongo, R Umeton Geophysical Research Abstracts / Proceedings of Asia Oceania Geosciences …, 2007 | 1* | 2007 |
