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- Meng-Meng Zhang, Dan Wang, Feng Lu, Rong Zhao, Xun Ye, Lin He, Li Ai, Chun-Jie Wu:
Identification of the active substances and mechanisms of ginger for the treatment of colon cancer based on network pharmacology and molecular docking. 1
- Congmin Xu, Man Zhou, Zhongjie Xie, Mo Li, Xi Zhu, Huaiqiu Zhu:
LightCUD: a program for diagnosing IBD based on human gut microbiome data. 2
- Ji-Yong An, Fanrong Meng, Zi-Ji Yan:
An efficient computational method for predicting drug-target interactions using weighted extreme learning machine and speed up robot features. 3
- Ye Emma Zohner, Jeffrey S. Morris:
COVID-TRACK: world and USA SARS-COV-2 testing and COVID-19 tracking. 4
- Kinza Rian, Marina Esteban-Medina, Marta R. Hidalgo, Cankut Çubuk, Matias M. Falco, Carlos Loucera, Devrim Gunyel, Marek Ostaszewski, María Peña-Chilet, Joaquín Dopazo:
Mechanistic modeling of the SARS-CoV-2 disease map. 5
- Geonseok Lee, Kichun Lee:
Feature selection using distributions of orthogonal PLS regression vectors in spectral data. 7
- Yuichi Sei, Akihiko Ohsuga:
Privacy-preserving chi-squared test of independence for small samples. 6
- Jason H. Moore:
Empowering the data science scientist. 8
- Alena Orlenko, Jason H. Moore:
A comparison of methods for interpreting random forest models of genetic association in the presence of non-additive interactions. 9
- Zejin Wang, Jing Liu, Xi Chen, Guoqing Li, Hua Han:
Sparse self-attention aggregation networks for neural sequence slice interpolation. 10
- Davide Chicco, Luca Oneto:
Data analytics and clinical feature ranking of medical records of patients with sepsis. 12
- Anas Belouali, Samir Gupta, Vaibhav Sourirajan, Jiawei Yu, Nathaniel Allen, Adil Alaoui, Mary Ann Dutton, Matthew J. Reinhard:
Acoustic and language analysis of speech for suicidal ideation among US veterans. 11
- Gianluca Moro, Marco Masseroli:
Gene function finding through cross-organism ensemble learning. 14
- Shabir Moosa, Abbes Amira, Sabri Boughorbel:
DASSI: differential architecture search for splice identification from DNA sequences. 15
- Fentaw Abegaz, François Van Lishout, Jestinah M. Mahachie John, Kridsadakorn Chaichoompu, Archana Bhardwaj, Diane Duroux, Elena S. Gusareva, Zhi Wei, Hakon Hakonarson, Kristel Van Steen:
Performance of model-based multifactor dimensionality reduction methods for epistasis detection by controlling population structure. 16
- Jung Wun Lee, Seungyeoun Lee:
A comparative study on the unified model based multifactor dimensionality reduction methods for identifying gene-gene interactions associated with the survival phenotype. 17
- Christopher Toh, James P. Brody:
Genetic risk score for ovarian cancer based on chromosomal-scale length variation. 18
- Saeed Salem, Mohammed Alokshiya, Mohammad Al Hasan:
RASMA: a reverse search algorithm for mining maximal frequent subgraphs. 19
- Brianna Sierra Chrisman, Kelley M. Paskov, Nate Tyler Stockham, Kevin Tabatabaei, Jae-Yoon Jung, Peter Washington, Maya Varma, Min Woo Sun, Sepideh Maleki, Dennis P. Wall:
Indels in SARS-CoV-2 occur at template-switching hotspots. 20
- Y. Wang, Y. M. Chu, Adel Thaljaoui, Yousef Ali Khan, Wathek Chammam, Syed Zaheer Abbas:
A multi-feature hybrid classification data mining technique for human-emotion. 21
- Jason H. Moore, Van Q. Truong, Ashley B. Robbins, David Nicholson, Clar Lynda Williams-Devane:
Ten important roles for academic leaders to promote equity, diversity, and inclusion in data science. 22
- Ashwath Radhachandran, Anurag Garikipati, Nicole S. Zelin, Emily Pellegrini, Sina Ghandian, Jacob S. Calvert, Jana L. Hoffman, Qingqing Mao, Ritankar Das:
Prediction of short-term mortality in acute heart failure patients using minimal electronic health record data. 23
- Peng Qiu, Yixuan Li, Kai Liu, Jinbao Qin, Kaichuang Ye, Tao Chen, Xinwu Lu:
Prescreening and treatment of aortic dissection through an analysis of infinite-dimension data. 24
- Cláudia S. Constantino, Alexandra M. Carvalho, Susana Vinga:
Coupling sparse Cox models with clustering of longitudinal transcriptomics data for trauma prognosis. 25
- Seema Singh Saharan, Pankaj Nagar, Kate Townsend Creasy, Eveline O. Stock, James Feng, Mary J. Malloy, John P. Kane:
Machine learning and statistical approaches for classification of risk of coronary artery disease using plasma cytokines. 26
- Davide Chicco, Niklas Tötsch, Giuseppe Jurman:
The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation. 13
- Kelley M. Paskov, Jae-Yoon Jung, Brianna Sierra Chrisman, Nate Tyler Stockham, Peter Washington, Maya Varma, Min Woo Sun, Dennis P. Wall:
Estimating sequencing error rates using families. 27
- Mahyar Sharifi, Toktam Khatibi, Mohammad Hassan Emamian, Somayeh Sadat, Hassan Hashemi, Akbar Fotouhi:
Development of glaucoma predictive model and risk factors assessment based on supervised models.
- Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja:
Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection.
- Sebastian Racedo, Ivan Portnoy, Jorge I. Vélez, Homero San-Juan-Vergara, Marco E. Sanjuan, Eduardo E. Zurek:
A new pipeline for structural characterization and classification of RNA-Seq microbiome data.
- Maya Varma, Kelley M. Paskov, Brianna Sierra Chrisman, Min Woo Sun, Jae-Yoon Jung, Nate Tyler Stockham, Peter Washington, Dennis P. Wall:
A maximum flow-based network approach for identification of stable noncoding biomarkers associated with the multigenic neurological condition, autism.
- Chih-Wei Chung, Tzu-Hung Hsiao, Chih-Jen Huang, Yen-Ju Chen, Hsin-Hua Chen, Ching-Heng Lin, Seng-Cho Chou, Tzer-Shyong Chen, Yu-Fang Chung, Hwai-I Yang, Yi-Ming Chen:
Machine learning approaches for the genomic prediction of rheumatoid arthritis and systemic lupus erythematosus.
- Theodore G. Drivas, Anastasia Lucas, Marylyn D. Ritchie:
eQTpLot: a user-friendly R package for the visualization of colocalization between eQTL and GWAS signals.
- Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh:
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient.
- Miquel Ensenyat-Mendez, Sandra Íñiguez-Muñoz, Borja Sesé, Diego M. Marzese:
Correction to: iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes.
- Miquel Ensenyat-Mendez, Sandra Íñiguez-Muñoz, Borja Sesé, Diego M. Marzese:
iGlioSub: an integrative transcriptomic and epigenomic classifier for glioblastoma molecular subtypes.
- Mila Glavaski, Lazar U. Velicki:
Humans and machines in biomedical knowledge curation: hypertrophic cardiomyopathy molecular mechanisms' representation.
- Nicholas Giangreco, Nicholas P. Tatonetti:
Evaluating risk detection methods to uncover ontogenic-mediated adverse drug effect mechanisms in children.
- Zhixuan Zeng, Shuo Yao, Jianfei Zheng, Xun Gong:
Development and validation of a novel blending machine learning model for hospital mortality prediction in ICU patients with Sepsis.
- Jun Ma, Alison A. Motsinger-Reif:
Prediction of synergistic drug combinations using PCA-initialized deep learning.
- Lihong Peng, Ruya Yuan, Ling Shen, Pengfei Gao, Liqian Zhou:
LPI-EnEDT: an ensemble framework with extra tree and decision tree classifiers for imbalanced lncRNA-protein interaction data classification.
- Qian Yan, Wenjiang Zheng, Boqing Wang, Baoqian Ye, Huiyan Luo, Xinqian Yang, Ping Zhang, Xiongwen Wang:
A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma.
- Scott Lewis, Andrea Nash, Qinghong Li, Tae-Hyuk Ahn:
Comparison of 16S and whole genome dog microbiomes using machine learning.
- Erika Cantor, Rodrigo Salas, Harvey Rosas, Sandra Guauque-Olarte:
Biological knowledge-slanted random forest approach for the classification of calcified aortic valve stenosis.
- Jacqueline Michelle Beinecke, Dominik Heider:
Gaussian noise up-sampling is better suited than SMOTE and ADASYN for clinical decision making.
- Ben Omega Petrazzini, Hugo Naya, Fernando Lopez-Bello, Gustavo E. Vazquez, Lucía Spangenberg:
Evaluation of different approaches for missing data imputation on features associated to genomic data.
- Juliana Alves Pegoraro, Sophie Lavault, Nicolas Wattiez, Thomas Similowski, Jésus Gonzalez-Bermejo, Etienne Birmelé:
Machine-learning based feature selection for a non-invasive breathing change detection.
- Sankalp Jain, Amit Saxena, Suprit Hesarur, Kirti Bhadhadhara, Neeraj Bharti, Sunitha Manjari Kasibhatla, Uddhavesh Sonavane, Rajendra Joshi:
GenoVault: a cloud based genomics repository.
- Arnaud Nguembang Fadja, Fabrizio Riguzzi, Giorgio Bertorelle, Emiliano Trucchi:
Identification of natural selection in genomic data with deep convolutional neural network.
- Shuanglong Fan, Zhiqiang Zhao, Yanbo Zhang, Hongmei Yu, ChuChu Zheng, XueQian Huang, Zhenhuan Yang, Meng Xing, Qing Lu, Yanhong Luo:
Probability calibration-based prediction of recurrence rate in patients with diffuse large B-cell lymphoma.
- Hao He, Yatong Zhou, Yue Chi, Jingfei He:
Prediction of MoRFs based on sequence properties and convolutional neural networks.
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