Typical and atypical pathology in primary progressive aphasia variants. Spinelli EG, Mandelli ML, Miller ZA, Santos-Santos MA, Wilson SM, Agosta F, Grinberg LT, Huang EJ, Trojanowski JQ, Meyer M, Henry ML, Comi G, Rabinovici G, Rosen HJ, Filippi M, Miller BL, Seeley WW, Gorno-Tempini ML (2017) Ann Neurol 81: 430-443 Semi-supervised learning improves gene expression-based prediction of cancer recurrence. Shi M, Zhang B (2011) Bioinformatics 27: 3017-23 An adaptive classification model for peptide identification. Liang X, Xia Z, Jian L, Niu X, Link A (2015) BMC Genomics 16 Suppl 11: S1 Sequence Characteristics Distinguish Transcribed Enhancers from Promoters and Predict Their Breadth of Activity. Colbran LL, Chen L, Capra JA (2019) Genetics 211: 1205-1217 A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients. Shi M, Beauchamp RD, Zhang B (2012) PLoS One 7: e41292 Large-scale prediction of adverse drug reactions using chemical, biological, and phenotypic properties of drugs. Liu M, Wu Y, Chen Y, Sun J, Zhao Z, Chen XW, Matheny ME, Xu H (2012) J Am Med Inform Assoc 19: e28-35 Machine learning-based prediction of drug-drug interactions by integrating drug phenotypic, therapeutic, chemical, and genomic properties. Cheng F, Zhao Z (2014) J Am Med Inform Assoc 21: e278-86 Applying active learning to high-throughput phenotyping algorithms for electronic health records data. Chen Y, Carroll RJ, Hinz ER, Shah A, Eyler AE, Denny JC, Xu H (2013) J Am Med Inform Assoc 20: e253-9 Molecular signatures mostly associated with NK cells are predictive of relapse free survival in breast cancer patients. Ascierto ML, Idowu MO, Zhao Y, Khalak H, Payne KK, Wang XY, Dumur CI, Bedognetti D, Tomei S, Ascierto PA, Shanker A, Bear HD, Wang E, Marincola FM, De Maria A, Manjili MH (2013) J Transl Med 11: 145 Benchmarking ligand-based virtual High-Throughput Screening with the PubChem database. Butkiewicz M, Lowe EW, Mueller R, Mendenhall JL, Teixeira PL, Weaver CD, Meiler J (2013) Molecules 18: 735-56 Development of an automated phenotyping algorithm for hepatorenal syndrome. Koola JD, Davis SE, Al-Nimri O, Parr SK, Fabbri D, Malin BA, Ho SB, Matheny ME (2018) J Biomed Inform 80: 87-95
Hints: (1) double-click or double-tap to navigate to a node. (2) Grab a node and move it to arrange the graph.