Connection
Mary Yang to Algorithms
This is a "connection" page, showing publications Mary Yang has written about Algorithms.
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Connection Strength |
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2.071 |
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Zhang Y, Yang W, Li D, Yang JY, Guan R, Yang MQ. Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis. BMC Med Genomics. 2018 Nov 20; 11(Suppl 5):104.
Score: 0.494
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Zhang X, Wang T, Luo H, Yang JY, Deng Y, Tang J, Yang MQ. 3D protein structure prediction with genetic tabu search algorithm. BMC Syst Biol. 2010 May 28; 4 Suppl 1:S6.
Score: 0.275
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Zeng XQ, Li GZ, Wu GF, Yang JY, Yang MQ. Irrelevant gene elimination for partial least squares based dimension reduction by using feature probes. Int J Data Min Bioinform. 2009; 3(1):85-103.
Score: 0.249
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Li GZ, Meng HH, Lu WC, Yang JY, Yang MQ. Asymmetric bagging and feature selection for activities prediction of drug molecules. BMC Bioinformatics. 2008 May 28; 9 Suppl 6:S7.
Score: 0.239
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Yang MQ, Yang JY. Lecture notes: 2010 and beyond, the decade of high-performance computing for the next-generation sequence analysis. Int J Comput Biol Drug Des. 2009; 2(2):204-6.
Score: 0.066
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Yang JY, Yang MQ. Predicting protein disorder by analyzing amino acid sequence. BMC Genomics. 2008 Sep 16; 9 Suppl 2:S8.
Score: 0.061
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Zeng XQ, Li GZ, Yang JY, Yang MQ, Wu GF. Dimension reduction with redundant gene elimination for tumor classification. BMC Bioinformatics. 2008 May 28; 9 Suppl 6:S8.
Score: 0.060
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Yang MQ, Taylor J, Elnitski L. Comparative analyses of bidirectional promoters in vertebrates. BMC Bioinformatics. 2008 May 28; 9 Suppl 6:S9.
Score: 0.060
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Habib T, Zhang C, Yang JY, Yang MQ, Deng Y. Supervised learning method for the prediction of subcellular localization of proteins using amino acid and amino acid pair composition. BMC Genomics. 2008; 9 Suppl 1:S16.
Score: 0.058
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Yang JY, Yang MQ, Luo Z, Ma Y, Li J, Deng Y, Huang X. A hybrid machine learning-based method for classifying the Cushing's Syndrome with comorbid adrenocortical lesions. BMC Genomics. 2008; 9 Suppl 1:S23.
Score: 0.058
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Yang JY, Li GZ, Meng HH, Yang MQ, Deng Y. Improving prediction accuracy of tumor classification by reusing genes discarded during gene selection. BMC Genomics. 2008; 9 Suppl 1:S3.
Score: 0.058
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Liu Q, Yang J, Chen Z, Yang MQ, Sung AH, Huang X. Supervised learning-based tagSNP selection for genome-wide disease classifications. BMC Genomics. 2008; 9 Suppl 1:S6.
Score: 0.058
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Yang JY, Yang MQ, Dunker AK, Deng Y, Huang X. Investigation of transmembrane proteins using a computational approach. BMC Genomics. 2008; 9 Suppl 1:S7.
Score: 0.058
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Yang JY, Yang MQ. Identification of Intrinsically Unstructured Proteins using hierarchical classifier. Int J Data Min Bioinform. 2008; 2(2):121-33.
Score: 0.058
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Liu TY, Li GZ, Yang JY, Yang MQ. Feature selection for the imbalanced QSAR problems by using easyensemble. Int J Comput Biol Drug Des. 2008; 1(4):334-46.
Score: 0.058
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Yang F, Darsey JA, Ghosh A, Li HY, Yang MQ, Wang S. Artificial Intelligence and Cancer Drug Development. Recent Pat Anticancer Drug Discov. 2022; 17(1):2-8.
Score: 0.038
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He G, Liang Y, Chen Y, Yang W, Liu JS, Yang MQ, Guan R. A hotspots analysis-relation discovery representation model for revealing diabetes mellitus and obesity. BMC Syst Biol. 2018 12 14; 12(Suppl 7):116.
Score: 0.031
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Guan R, Wang X, Yang MQ, Zhang Y, Zhou F, Yang C, Liang Y. Multi-label Deep Learning for Gene Function Annotation in Cancer Pathways. Sci Rep. 2018 01 10; 8(1):267.
Score: 0.029
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Wang L, Yang MQ, Yang JY. Prediction of DNA-binding residues from protein sequence information using random forests. BMC Genomics. 2009 Jul 07; 10 Suppl 1:S1.
Score: 0.016
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Liu Q, Sung AH, Qiao M, Chen Z, Yang JY, Yang MQ, Huang X, Deng Y. Comparison of feature selection and classification for MALDI-MS data. BMC Genomics. 2009 Jul 07; 10 Suppl 1:S3.
Score: 0.016
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Pirooznia M, Gong P, Yang JY, Yang MQ, Perkins EJ, Deng Y. ILOOP--a web application for two-channel microarray interwoven loop design. BMC Genomics. 2008 Sep 16; 9 Suppl 2:S11.
Score: 0.015
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Li GZ, Bu HL, Yang MQ, Zeng XQ, Yang JY. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis. BMC Genomics. 2008 Sep 16; 9 Suppl 2:S24.
Score: 0.015
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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