Page 75 - TD-4-3
P. 75
Tumor Discovery Highly accurate gene panels for cancer screening
21. Kaytoue M, Kuznetsov SO, Napoli A, Duplessis S. Mining Notes in Computer Science. Vol. 4062. Berlin, Heidelberg:
gene expression data with pattern structures in formal Springer; 2006. p. 778-785.
concept analysis. Inf Sci. 2011;181(10):1989-2001.
doi: 10.1007/11795131_113
doi: 10.1016/j.ins.2010.07.007
32. Mishra D, Dash R, Rath AK, Acharya M. Feature selection
22. González-Calabozo JM, Valverde-Albacete FJ, Peláez- in gene expression data using principal component analysis
Moreno C. Interactive knowledge discovery and data and rough set theory. In: Arabnia HR, Tran QN, editors.
mining on genomic expression data with numeric formal Software Tools and Algorithms for Biological Systems.
concept analysis. BMC Bioinform. 2016;17(1):374. Advances in Experimental Medicine and Biology. Vol. 696.
New York: Springer; 2011. p. 91-100.
doi: 10.1186/s12859-016-1234-z
doi: 10.1007/978-1-4419-7046-6_10
23. Singh PK, Kumar CA, Gani AA. Comprehensive survey on
formal concept analysis, its research trends, and applications. 33. Pati SK, Das AK, Ghosh A. Gene Selection Using Multi-
Int J Appl Math Comput Sci. 2016;26(2):495-516. objective Genetic Algorithm Integrating Cellular Automata
and Rough Set Theory. In: Panigrahi BK, Suganthan, PN,
doi: 10.1515/amcs-2016-0035
Das S, Dash SS, editors. Swarm, Evolutionary, and Memetic
24. Raza K. Formal concept analysis for knowledge Computing. SEMCCO 2013. Lecture Notes in Computer
discovery from biological data. Int J Data Min Bioinform. Science. Vol. 8298. Cham: Springer; 2013. p. 144-155.
2017;18(4):281.
doi: 10.1007/978-3-319-03756-1_13
doi: 10.1504/IJDMB.2017.088138
34. Zhang Q, Xie Q, Wang G. A survey on rough set
25. Ferreira LM, Pinto CLN, Dias SM, Nobre CN, Zárate theory and its applications. CAAI Trans Intell Technol.
LE. Extraction of Conservative Rules for Translation 2016;1(4):323-333.
Initiation Site Prediction Using Formal Concept Analysis. doi: 10.1016/j.trit.2016.11.001
In: Proceedings of the 19 International Conference on
th
Enterprise Information Systems (ICEIS). Vol. 1. SciTePress; 35. Chen Y, Zhang Z, Zheng J, Ma Y, Xue Y. Gene selection for
2017. p. 265-271. tumor classification using neighborhood rough sets and
entropy measures. J Biomed Inform. 2017;67:59-68.
doi: 10.5220/0006326202650271
doi: 10.1016/j.jbi.2017.02.007
26. Zhao M, Zhang S, Li W, Chen G. Matching biomedical
ontologies based on formal concept analysis. J Biomed 36. Sun L, Zhang X, Xu J, Wang W, Liu R. A Gene selection
Semantics. 2018;9(1):11. approach based on the fisher linear discriminant and the
neighborhood rough set. Bioengineered. 2018;9(1):144-151.
doi: 10.1186/s13326-018-0178-9
doi: 10.1080/21655979.2017.1403678
27. Roscoe S, Khatri M, Voshall A, Batra S, Kaur S, Deogun J.
Formal concept analysis applications in bioinformatics. 37. Saha S, Roy S, Ghosh A, Dey KN. Gene-Gene Interaction
ACM Comput Surv. 2023;55(8):1-40. Analysis: Correlation, Relative Entropy and Rough Set
Theory Based Approach. In: Bioinformatics and Biomedical
doi: 10.1145/3554728
Engineering: 6 International Work-Conference, IWBBIO
th
28. Maji P, Paul S. Rough set based maximum relevance- 2018. Proceedings, Part II. Granada, Spain: Springer-Verlag;
maximum significance criterion and gene selection from 2018. p. 397-408.
microarray data. Int J Approx Reason. 2011;52(3):408-426.
doi: 10.1007/978-3-319-78759-6_36
doi: 10.1016/j.ijar.2010.09.006
38. Patil S, Balmuri KR, Frnda J, Parameshachari BD,
29. Midelfart H, Komorowski J, Nørsett K, Yadetie F, Konda S, Nedoma J. Identification of triple-negative breast
Sandovik AK, Lægreid A. Learning rough set classifiers cancer genes using rough set-based feature selection algorithm
from gene expressions and clinical data. Fundam Inform. and ensemble classifier. Hum Centric Comput Inf Sci. 2022;12:54.
2002;53(2):155-183.
doi: 10.22967/HCIS.2022.12.054
doi: 10.3233/FUN-2002-53204
39. Majumder S, Thakran Y, Pal V, Singh K. Fuzzy and rough set
30. Dai J, Xu Q. Attribute selection based on information gain theory based computational framework for mining genetic
ratio in fuzzy rough set theory with application to tumor interaction triplets from gene expression profiles for lung
classification. Appl Soft Comput. 2013;13(1):211-221. adenocarcinoma. IEEE/ACM Trans Comput Biol Bioinform.
2022;19(6):3469-3481.
doi: 10.1016/j.asoc.2012.07.029
doi: 10.1109/TCBB.2021.3120844
31. Li D, Zhang W. Gene selection using rough set theory.
In Wang GY, Peters JF, Skowron A, Yao Y, editors. Rough 40. Duntsch N, Gediga G. Modal-style Operators in Qualitative
Sets and Knowledge Technology. RSKT 2006. Lecture Data Analysis. In: 2002 IEEE International Conference
Volume 4 Issue 3 (2025) 67 doi: 10.36922/TD025190035

