TY - BOOK AU - Hoopes, L. PY - 2008 DA - 2008// TI - Genetic diagnosis: DNA microarrays and cancer ID - Hoopes2008 ER - TY - STD TI - S. H. Aljahdali and M. E. El-Telbany, "Bio-inspired machine learning in microarray gene selection and cancer classification," in Signal Processing and Information Technology (ISSPIT), 2009 IEEE International Symposium on, 2009, pp. 339–343: IEEE. ID - ref2 ER - TY - STD TI - C. A. Kumar and S. Ramakrishnan, "Binary Classification of cancer microarray gene expression data using extreme learning machines," in Computational Intelligence and Computing Research (ICCIC), 2014 IEEE International Conference on, 2014, pp. 1–4: IEEE. ID - ref3 ER - TY - JOUR AU - Bhola, A. AU - Tiwari, A. K. PY - 2015 DA - 2015// TI - Machine learning based approaches for Cancer classification using gene expression data JO - Mach Learn Appl VL - 2 ID - Bhola2015 ER - TY - STD TI - S.-B. Cho and H.-H. Won, "machine learning in DNA microarray analysis for cancer classification," in Proceedings of the First Asia-Pacific bioinformatics conference on Bioinformatics 2003-Volume 19, 2003, pp. 189-198: Australian computer society, Inc. ID - ref5 ER - TY - CHAP AU - Azzawi, H. a. s. s. e. e. b. AU - Hou, J. i. n. g. y. u. AU - Alanni, R. u. s. s. u. l. AU - Xiang, Y. o. n. g. PY - 2019 DA - 2019// TI - A Hybrid Neural Network Approach for Lung Cancer Classification with Gene Expression Dataset and Prior Biological Knowledge BT - Machine Learning for Networking PB - Springer International Publishing CY - Cham UR - https://doi.org/10.1007/978-3-030-19945-6_20 DO - 10.1007/978-3-030-19945-6_20 ID - Azzawi2019 ER - TY - JOUR AU - Han, F. AU - Sun, W. AU - Ling, Q. -. H. PY - 2014 DA - 2014// TI - A novel strategy for gene selection of microarray data based on gene-to-class sensitivity information JO - PloS one VL - 9 UR - https://doi.org/10.1371/journal.pone.0097530 DO - 10.1371/journal.pone.0097530 ID - Han2014 ER - TY - JOUR AU - Wang, Y. PY - 2005 DA - 2005// TI - Gene selection from microarray data for cancer classification—a machine learning approach JO - Comput Biol Chem VL - 29 UR - https://doi.org/10.1016/j.compbiolchem.2004.11.001 DO - 10.1016/j.compbiolchem.2004.11.001 ID - Wang2005 ER - TY - JOUR AU - Liu, Q. PY - 2011 DA - 2011// TI - Gene selection and classification for cancer microarray data based on machine learning and similarity measures JO - BMC Genomics VL - 12 UR - https://doi.org/10.1186/1471-2164-12-S5-S1 DO - 10.1186/1471-2164-12-S5-S1 ID - Liu2011 ER - TY - STD TI - Y. Lu, L. Wang, P. Liu, P. Yang, and M. You, "Gene-expression signature predicts postoperative recurrence in stage I non-small cell lung cancer patients," vol. 7, no. 1, p. e30880, 2012. ID - ref10 ER - TY - STD TI - W. Liu et al., "Identification of genes associated with cancer progression and prognosis in lung adenocarcinoma: Analyses based on microarray from Oncomine and The Cancer Genome Atlas databases," vol. 7, no. 2, p. e00528, 2019. ID - ref11 ER - TY - JOUR AU - Hayes, J. o. s. i. e. AU - Peruzzi, P. i. e. r. P. a. o. l. o. AU - Lawler, S. e. a. n. PY - 2014 DA - 2014// TI - MicroRNAs in cancer: biomarkers, functions and therapy JO - Trends in Molecular Medicine VL - 20 UR - https://doi.org/10.1016/j.molmed.2014.06.005 DO - 10.1016/j.molmed.2014.06.005 ID - Hayes2014 ER - TY - BOOK AU - Wang, W. PY - 2019 DA - 2019// TI - The value of plasma-based microRNAs as diagnostic biomarkers for ovarian cancer UR - https://doi.org/10.1016/j.amjms.2019.07.005 DO - 10.1016/j.amjms.2019.07.005 ID - Wang2019 ER - TY - JOUR AU - Das, S. AU - Meher, P. K. AU - Rai, A. AU - Bhar, L. M. AU - Mandal, B. N. PY - 2017 DA - 2017// TI - Statistical approaches for gene selection, Hub gene identification and module interaction in gene co-expression network analysis: An application to aluminum stress in soybean (Glycine max L.) JO - PloS one VL - 12 UR - https://doi.org/10.1371/journal.pone.0169605 DO - 10.1371/journal.pone.0169605 ID - Das2017 ER - TY - JOUR AU - Mundra, P. A. AU - Rajapakse, J. C. PY - 2010 DA - 2010// TI - SVM-RFE with MRMR filter for gene selection JO - IEEE Trans Nanobioscience VL - 9 UR - https://doi.org/10.1109/TNB.2009.2035284 DO - 10.1109/TNB.2009.2035284 ID - Mundra2010 ER - TY - STD TI - H. Mhamdi and F. Mhamdi, "Feature selection methods on biological knowledge discovery and data mining: A survey," in Database and Expert Systems Applications (DEXA), 2014 25th International Workshop on, 2014, pp. 46–50: IEEE. ID - ref16 ER - TY - JOUR AU - Chandrashekar, G. AU - Sahin, F. PY - 2014 DA - 2014// TI - A survey on feature selection methods JO - Comput Electrical Eng VL - 40 UR - https://doi.org/10.1016/j.compeleceng.2013.11.024 DO - 10.1016/j.compeleceng.2013.11.024 ID - Chandrashekar2014 ER - TY - JOUR AU - Sheikhpour, R. AU - Sarram, M. A. AU - Gharaghani, S. AU - Chahooki, M. A. Z. PY - 2017 DA - 2017// TI - A survey on semi-supervised feature selection methods JO - Pattern Recogn VL - 64 UR - https://doi.org/10.1016/j.patcog.2016.11.003 DO - 10.1016/j.patcog.2016.11.003 ID - Sheikhpour2017 ER - TY - STD TI - W. Wan and J. B. Birch, "An improved hybrid genetic algorithm with a new local search procedure," Journal of Applied Mathematics, vol 2013, 2013. ID - ref19 ER - TY - JOUR AU - Apolloni, J. AU - Leguizamón, G. AU - Alba, E. PY - 2016 DA - 2016// TI - Two hybrid wrapper-filter feature selection algorithms applied to high-dimensional microarray experiments JO - Appl Soft Comput VL - 38 UR - https://doi.org/10.1016/j.asoc.2015.10.037 DO - 10.1016/j.asoc.2015.10.037 ID - Apolloni2016 ER - TY - JOUR AU - Han, F. PY - 2017 DA - 2017// TI - A gene selection method for microarray data based on binary PSO encoding gene-to-class sensitivity information JO - IEEE/ACM Trans Comput Biol Bioinform VL - 14 UR - https://doi.org/10.1109/TCBB.2015.2465906 DO - 10.1109/TCBB.2015.2465906 ID - Han2017 ER - TY - JOUR AU - Alshamlan, H. a. l. a. AU - Badr, G. h. a. d. a. AU - Alohali, Y. o. u. s. e. f. PY - 2015 DA - 2015// TI - mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling JO - BioMed Research International VL - 2015 UR - https://doi.org/10.1155/2015/604910 DO - 10.1155/2015/604910 ID - Alshamlan2015 ER - TY - JOUR AU - Moradi, P. AU - Gholampour, M. PY - 2016 DA - 2016// TI - A hybrid particle swarm optimization for feature subset selection by integrating a novel local search strategy JO - Appl Soft Comput VL - 43 UR - https://doi.org/10.1016/j.asoc.2016.01.044 DO - 10.1016/j.asoc.2016.01.044 ID - Moradi2016 ER - TY - STD TI - J. Yang and V. Honavar, "Feature subset selection using a genetic algorithm," in Feature extraction, construction and selection: Springer, 1998, pp. 117–136. ID - ref24 ER - TY - JOUR AU - Koza, J. R. PY - 1994 DA - 1994// TI - Genetic programming as a means for programming computers by natural selection JO - Stat Comput VL - 4 UR - https://doi.org/10.1007/BF00175355 DO - 10.1007/BF00175355 ID - Koza1994 ER - TY - STD TI - Y. Shi, "Particle swarm optimization: developments, applications and resources," in evolutionary computation, 2001. Proceedings of the 2001 Congress on, 2001, vol. 1, pp. 81–86: IEEE. ID - ref26 ER - TY - STD TI - D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Technical report-tr06, Erciyes university, engineering faculty, computer engineering department 2005. ID - ref27 ER - TY - STD TI - R. Alanni, J. Hou, H. Azzawi, and Y. Xiang, "A novel gene selection algorithm for cancer classification using microarray datasets," BMC Medical Genomics, vol. 12, no. 1, p. 10, 2019. ID - ref28 ER - TY - STD TI - C. Ferreira and U. Gepsoft, "what is gene expression programming," ed, 2008. ID - ref29 ER - TY - JOUR AU - Azzawi, H. AU - Hou, J. AU - Xiang, Y. AU - Alanni, R. PY - 2016 DA - 2016// TI - Lung cancer prediction from microarray data by gene expression programming JO - IET Syst Biol VL - 10 UR - https://doi.org/10.1049/iet-syb.2015.0082 DO - 10.1049/iet-syb.2015.0082 ID - Azzawi2016 ER - TY - JOUR AU - Alanni, R. AU - Hou, J. AU - Abdu-aljabar, R. D. AU - Xiang, Y. PY - 2017 DA - 2017// TI - Prediction of NSCLC recurrence from microarray data with GEP JO - IET Syst Biol VL - 11 UR - https://doi.org/10.1049/iet-syb.2016.0033 DO - 10.1049/iet-syb.2016.0033 ID - Alanni2017 ER - TY - CHAP AU - Alanni, R. AU - Hou, J. AU - Azzawi, H. AU - Xiang, Y. ED - Lee, R. PY - 2019 DA - 2019// TI - New gene selection method using gene expression programing approach on microarray data sets BT - Computer and information science PB - Springer International Publishing CY - Cham UR - https://doi.org/10.1007/978-3-319-98693-7_2 DO - 10.1007/978-3-319-98693-7_2 ID - Alanni2019 ER - TY - STD TI - H. Azzawi, J. Hou, R. Alanni, and Y. Xiang, "SBC: A New Strategy for Multiclass Lung Cancer Classification Based on Tumour Structural Information and Microarray Data," in 17th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2018), 2018, pp. 68–73: IEEE. ID - ref33 ER - TY - STD TI - Alanni R, Hou J, Azzawi H, Xiang Y. Cancer adjuvant chemotherapy prediction model for non-small cell lung cancer. IET Syst Biol. 2019. ID - ref34 ER - TY - STD TI - R. Alanni, J. Hou, H. Azzawi, and Y. Xiang, "RISK CLASSIFICATION FOR NSCLC SURVIVAL USING MICROARRAY AND CLINICAL DATA," presented at THE 207TH THE IIER INTERNATIONAL CONFERENCE, 12-12-2018, 2019. Available: http://worldresearchlibrary.org/proceeding.php?pid=2429 UR - http://worldresearchlibrary.org/proceeding.php?pid=2429 ID - ref35 ER - TY - STD TI - C. Ferreira, "Gene expression programming in problem solving," in Soft computing and industry: Springer, 2002, pp. 635–653. ID - ref36 ER - TY - STD TI - H. Azzawi, J. Hou, R. Alanni, Y. Xiang, R. Abdu-Aljabar, and A. Azzawi, "Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets," in International Conference on Advanced Data Mining and Applications, 2017, pp. 541–553: Springer. ID - ref37 ER - TY - JOUR AU - Ferreira, C. PY - 2001 DA - 2001// TI - Gene expression programming: a new adaptive algorithm for solving problems JO - Complex Systems VL - 13 ID - Ferreira2001 ER - TY - JOUR AU - Mohamad, M. S. AU - Omatu, S. AU - Deris, S. AU - Yoshioka, M. PY - 2011 DA - 2011// TI - A modified binary particle swarm optimization for selecting the small subset of informative genes from gene expression data JO - IEEE Trans Inf Technol Biomed VL - 15 UR - https://doi.org/10.1109/TITB.2011.2167756 DO - 10.1109/TITB.2011.2167756 ID - Mohamad2011 ER - TY - JOUR AU - Yang, C. -. H. AU - Chuang, L. -. Y. AU - Yang, C. H. PY - 2010 DA - 2010// TI - IG-GA: a hybrid filter/wrapper method for feature selection of microarray data JO - J Med Biol Eng VL - 30 ID - Yang2010 ER - TY - STD TI - Lai C-M, Yeh W-C, Chang C-Y. Gene selection using information gain and improved simplified swarm optimization. Neurocomputing. 2016. ID - ref41 ER - TY - STD TI - M. S. Mohamad, S. Omatu, S. Deris, M. Yoshioka, A. Abdullah, and Z. Ibrahim, "An enhancement of binary particle swarm optimization for gene selection in classifying cancer classes," Algorithms for Molecular Biology, vol. 8, no. 1, p. 1, 2013. ID - ref42 ER - TY - STD TI - J. M. Moosa, R. Shakur, M. Kaykobad, and M. S. Rahman, "Gene selection for cancer classification with the help of bees," BMC Medical Genomics, vol. 9, no. 2, p. 47, 2016. ID - ref43 ER - TY - JOUR AU - Su, A. I. PY - 2001 DA - 2001// TI - Molecular classification of human carcinomas by use of gene expression signatures JO - Cancer Res VL - 61 ID - Su2001 ER - TY - JOUR AU - Staunton, J. E. PY - 2001 DA - 2001// TI - Chemosensitivity prediction by transcriptional profiling JO - Proc Natl Acad Sci VL - 98 UR - https://doi.org/10.1073/pnas.191368598 DO - 10.1073/pnas.191368598 ID - Staunton2001 ER - TY - STD TI - S. L. Pomeroy et al., "Prediction of central nervous system embryonal tumour outcome based on gene expression," Nature, vol. 415, no. 6870, p. 436, 2002. ID - ref46 ER - TY - JOUR AU - Nutt, C. L. PY - 2003 DA - 2003// TI - Gene expression-based classification of malignant gliomas correlates better with survival than histological classification JO - Cancer Res VL - 63 ID - Nutt2003 ER - TY - JOUR AU - Golub, T. R. PY - 1999 DA - 1999// TI - Molecular classification of cancer: class discovery and class prediction by gene expression monitoring JO - science VL - 286 UR - https://doi.org/10.1126/science.286.5439.531 DO - 10.1126/science.286.5439.531 ID - Golub1999 ER - TY - JOUR AU - Armstrong, S. c. o. t. t. A. AU - Staunton, J. a. n. e. E. AU - Silverman, L. e. w. i. s. B. AU - Pieters, R. o. b. AU - den Boer, M. o. n. i. q. u. e. L. AU - Minden, M. a. r. k. D. AU - Sallan, S. t. e. p. h. e. n. E. AU - Lander, E. r. i. c. S. AU - Golub, T. o. d. d. R. AU - Korsmeyer, S. t. a. n. l. e. y. J. PY - 2001 DA - 2001// TI - MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia JO - Nature Genetics VL - 30 UR - https://doi.org/10.1038/ng765 DO - 10.1038/ng765 ID - Armstrong2001 ER - TY - JOUR AU - Bhattacharjee, A. PY - 2001 DA - 2001// TI - Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses JO - Proc Natl Acad Sci VL - 98 UR - https://doi.org/10.1073/pnas.191502998 DO - 10.1073/pnas.191502998 ID - Bhattacharjee2001 ER - TY - JOUR AU - Khan, J. PY - 2001 DA - 2001// TI - Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks JO - Nat Med VL - 7 UR - https://doi.org/10.1038/89044 DO - 10.1038/89044 ID - Khan2001 ER - TY - JOUR AU - Singh, D. PY - 2002 DA - 2002// TI - Gene expression correlates of clinical prostate cancer behavior JO - Cancer Cell VL - 1 UR - https://doi.org/10.1016/S1535-6108(02)00030-2 DO - 10.1016/S1535-6108(02)00030-2 ID - Singh2002 ER - TY - JOUR AU - Shipp, M. A. PY - 2002 DA - 2002// TI - Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning JO - Nat Med VL - 8 UR - https://doi.org/10.1038/nm0102-68 DO - 10.1038/nm0102-68 ID - Shipp2002 ER - TY - STD TI - J. Thomas, "gene expression programming for Java," ed, 2010. ID - ref54 ER - TY - JOUR AU - Rajaguru, H. AU - Ganesan, K. AU - Bojan, V. K. PY - 2016 DA - 2016// TI - Earlier detection of cancer regions from MR image features and SVM classifiers JO - Int J Imaging Syst Technol VL - 26 UR - https://doi.org/10.1002/ima.22177 DO - 10.1002/ima.22177 ID - Rajaguru2016 ER - TY - STD TI - H. A. Le Thi and M. C. Nguyen, "DCA based algorithms for feature selection in multi-class support vector machine," Annals of Operations Research, journal article vol. 249, no. 1, pp. 273–300, February 01 2017. ID - ref56 ER - TY - JOUR AU - Priyadarsini, R. P. AU - Valarmathi, M. AU - Sivakumari, S. PY - 2011 DA - 2011// TI - Gain ratio based feature selection method for privacy preservation JO - ICTACT J Soft Comput VL - 1 ID - Priyadarsini2011 ER - TY - JOUR AU - Karegowda, A. G. AU - Manjunath, A. AU - Jayaram, M. PY - 2010 DA - 2010// TI - Comparative study of attribute selection using gain ratio and correlation based feature selection JO - Int J Inform Technol Knowl Manag VL - 2 ID - Karegowda2010 ER - TY - JOUR AU - Yang, P. AU - Zhou, B. B. AU - Zhang, Z. AU - Zomaya, A. Y. PY - 2010 DA - 2010// TI - A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data JO - BMC Bioinformatics VL - 11 UR - https://doi.org/10.1186/1471-2105-11-5 DO - 10.1186/1471-2105-11-5 ID - Yang2010 ER - TY - JOUR AU - Suryamohan, K. AU - Halfon, M. S. PY - 2015 DA - 2015// TI - Identifying transcriptional cis-regulatory modules in animal genomes JO - Wiley Interdiscip Rev Dev Biol VL - 4 UR - https://doi.org/10.1002/wdev.168 DO - 10.1002/wdev.168 ID - Suryamohan2015 ER -