| One-class SVMs for document classification LM Manevitz, M Yousef Journal of machine Learning research 2 (Dec), 139-154, 2001 | 1945 | 2001 |
| One-class document classification via neural networks L Manevitz, M Yousef Neurocomputing 70 (7-9), 1466-1481, 2007 | 274 | 2007 |
| Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier M Yousef, M Nebozhyn, H Shatkay, S Kanterakis, LC Showe, MK Showe Bioinformatics 22 (11), 1325-1334, 2006 | 241 | 2006 |
| Epigenetic regulation of Kaposi's sarcoma-associated herpesvirus latency by virus-encoded microRNAs that target Rta and the cellular Rbl2-DNMT pathway F Lu, W Stedman, M Yousef, R Renne, PM Lieberman Journal of virology 84 (6), 2697-2706, 2010 | 232 | 2010 |
| Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment LJ Marcos-Zambrano, K Karaduzovic-Hadziabdic, T Loncar Turukalo, ... Frontiers in microbiology 12, 634511, 2021 | 224 | 2021 |
| Naïve Bayes for microRNA target predictions—machine learning for microRNA targets M Yousef, S Jung, AV Kossenkov, LC Showe, MK Showe Bioinformatics 23 (22), 2987-2992, 2007 | 193 | 2007 |
| Gene expression profiles in peripheral blood mononuclear cells can distinguish patients with non–small cell lung cancer from patients with nonmalignant lung disease MK Showe, A Vachani, AV Kossenkov, M Yousef, C Nichols, EV Nikonova, ... Cancer research 69 (24), 9202-9210, 2009 | 183 | 2009 |
| Recursive Cluster Elimination (RCE) for classification and feature selection from gene expression data M Yousef, S Jung, LC Showe, MK Showe BMC bioinformatics 8, 1-12, 2007 | 135 | 2007 |
| Quantitative PCR on 5 genes reliably identifies CTCL patients with 5% to 99% circulating tumor cells with 90% accuracy M Nebozhyn, A Loboda, L Kari, AH Rook, EC Vonderheid, S Lessin, ... Blood 107 (8), 3189-3196, 2006 | 117 | 2006 |
| Circulating monocytes in HIV-1-infected viremic subjects exhibit an antiapoptosis gene signature and virus-and host-mediated apoptosis resistance MS Giri, M Nebozyhn, A Raymond, B Gekonge, A Hancock, S Creer, ... The Journal of Immunology 182 (7), 4459-4470, 2009 | 103 | 2009 |
| Learning from positive examples when the negative class is undetermined-microRNA gene identification M Yousef, S Jung, LC Showe, MK Showe Algorithms for molecular biology 3, 1-9, 2008 | 94 | 2008 |
| A study of microRNAs in silico and in vivo: bioinformatics approaches to microRNA discovery and target identification M Yousef, L Showe, M Showe The FEBS journal 276 (8), 2150-2156, 2009 | 81 | 2009 |
| Computational methods for microRNA target prediction H Hamzeiy, J Allmer, M Yousef miRNomics: MicroRNA Biology and Computational Analysis, 207-221, 2014 | 66 | 2014 |
| Classification and biomarker identification using gene network modules and support vector machines M Yousef, M Ketany, L Manevitz, LC Showe, MK Showe BMC bioinformatics 10, 1-7, 2009 | 63 | 2009 |
| Application of biological domain knowledge based feature selection on gene expression data M Yousef, A Kumar, B Bakir-Gungor Entropy 23 (1), 2, 2020 | 56 | 2020 |
| Finite–element mesh generation using self–organizing neural networks L Manevitz, M Yousef, D Givoli Computer‐Aided Civil and Infrastructure Engineering 12 (4), 233-250, 1997 | 55 | 1997 |
| Increased metallothionein gene expression, zinc, and zinc-dependent resistance to apoptosis in circulating monocytes during HIV viremia AD Raymond, B Gekonge, MS Giri, A Hancock, E Papasavvas, J Chehimi, ... Journal of leukocyte biology 88 (3), 589-596, 2010 | 53 | 2010 |
| miRNomics: microRNA biology and computational analysis M Yousef, J Allmer Humana Press, 2014 | 48 | 2014 |
| Document classification on neural networks using only positive examples LM Manevitz, M Yousef Proceedings of the 23rd annual international ACM SIGIR conference on …, 2000 | 48 | 2000 |
| Computational methods for ab initio detection of microRNAs J Allmer, M Yousef Frontiers in genetics 3, 209, 2012 | 47 | 2012 |
Louise ShoweProfessor, Molecular Oncogenesis, The Wistar Institute在 wistar.org 的电子邮件经过验证
