266 related articles for article (PubMed ID: 29870335)
1. DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.
Mallik S; Bhadra T; Mukherji A; Mallik S; Bhadra T; Mukherji A; Mallik S; Bhadra T; Mukherji A
IEEE Trans Nanobioscience; 2018 Apr; 17(2):117-125. PubMed ID: 29870335
[TBL] [Abstract][Full Text] [Related]
2. Analyzing large gene expression and methylation data profiles using StatBicRM: statistical biclustering-based rule mining.
Maulik U; Mallik S; Mukhopadhyay A; Bandyopadhyay S
PLoS One; 2015; 10(4):e0119448. PubMed ID: 25830807
[TBL] [Abstract][Full Text] [Related]
3. RANWAR: rank-based weighted association rule mining from gene expression and methylation data.
Mallik S; Mukhopadhyay A; Maulik U
IEEE Trans Nanobioscience; 2015 Jan; 14(1):59-66. PubMed ID: 25265613
[TBL] [Abstract][Full Text] [Related]
4. Optimal ranking and directional signature classification using the integral strategy of multi-objective optimization-based association rule mining of multi-omics data.
Mallik S; Seth S; Si A; Bhadra T; Zhao Z
Front Bioinform; 2023; 3():1182176. PubMed ID: 37576714
[No Abstract] [Full Text] [Related]
5. Dynamic association rules for gene expression data analysis.
Chen SC; Tsai TH; Chung CH; Li WH
BMC Genomics; 2015 Oct; 16():786. PubMed ID: 26467206
[TBL] [Abstract][Full Text] [Related]
6. Mining Temporal Protein Complex Based on the Dynamic PIN Weighted with Connected Affinity and Gene Co-Expression.
Shen X; Yi L; Jiang X; He T; Hu X; Yang J
PLoS One; 2016; 11(4):e0153967. PubMed ID: 27100396
[TBL] [Abstract][Full Text] [Related]
7. Divide and Conquer Approach to Contact Map Overlap Problem Using 2D-Pattern Mining of Protein Contact Networks.
Koneru SV; Bhavani DS
IEEE/ACM Trans Comput Biol Bioinform; 2015; 12(4):729-37. PubMed ID: 26357311
[TBL] [Abstract][Full Text] [Related]
8. Identification of temporal association rules from time-series microarray data sets.
Nam H; Lee K; Lee D
BMC Bioinformatics; 2009 Mar; 10 Suppl 3(Suppl 3):S6. PubMed ID: 19344482
[TBL] [Abstract][Full Text] [Related]
9. A novel association rule mining approach using TID intermediate itemset.
Aqra I; Herawan T; Abdul Ghani N; Akhunzada A; Ali A; Bin Razali R; Ilahi M; Raymond Choo KK
PLoS One; 2018; 13(1):e0179703. PubMed ID: 29351287
[TBL] [Abstract][Full Text] [Related]
10. Text mining and visualisation of Protein-Protein Interactions.
Tsai FS
Int J Comput Biol Drug Des; 2011; 4(3):239-44. PubMed ID: 21778557
[TBL] [Abstract][Full Text] [Related]
11. Hash subgraph pairwise kernel for protein-protein interaction extraction.
Zhang Y; Lin H; Yang Z; Wang J; Li Y
IEEE/ACM Trans Comput Biol Bioinform; 2012; 9(4):1190-202. PubMed ID: 22595237
[TBL] [Abstract][Full Text] [Related]
12. Mining association rules with multiple minimum supports: a new mining algorithm and a support tuning mechanism.
Hu YH; Chen YL
Decis Support Syst; 2006 Oct; 42(1):1-24. PubMed ID: 32287563
[TBL] [Abstract][Full Text] [Related]
13. Multimodal Omics Data Integration Using Max Relevance--Max Significance Criterion.
Maji P; Mandal A
IEEE Trans Biomed Eng; 2017 Aug; 64(8):1841-1851. PubMed ID: 27834637
[TBL] [Abstract][Full Text] [Related]
14. The Mining Algorithm of Maximum Frequent Itemsets Based on Frequent Pattern Tree.
Mi X
Comput Intell Neurosci; 2022; 2022():7022168. PubMed ID: 35634074
[TBL] [Abstract][Full Text] [Related]
15. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.
Yang AC; Hsu HH; Lu MD; Tseng VS; Shih TK
Int J Data Min Bioinform; 2014; 10(2):121-45. PubMed ID: 25796734
[TBL] [Abstract][Full Text] [Related]
16. Construction and application of dynamic protein interaction network based on time course gene expression data.
Wang J; Peng X; Li M; Pan Y
Proteomics; 2013 Jan; 13(2):301-12. PubMed ID: 23225755
[TBL] [Abstract][Full Text] [Related]
17. High confidence rule mining for microarray analysis.
McIntosh T; Chawla S
IEEE/ACM Trans Comput Biol Bioinform; 2007; 4(4):611-623. PubMed ID: 17975272
[TBL] [Abstract][Full Text] [Related]
18. A mouse protein interactome through combined literature mining with multiple sources of interaction evidence.
Li X; Cai H; Xu J; Ying S; Zhang Y
Amino Acids; 2010 Apr; 38(4):1237-52. PubMed ID: 19669079
[TBL] [Abstract][Full Text] [Related]
19. ConGEMs: Condensed Gene Co-Expression Module Discovery Through Rule-Based Clustering and Its Application to Carcinogenesis.
Mallik S; Zhao Z
Genes (Basel); 2017 Dec; 9(1):. PubMed ID: 29283433
[TBL] [Abstract][Full Text] [Related]
20. Cross-Ontology multi-level association rule mining in the Gene Ontology.
Manda P; Ozkan S; Wang H; McCarthy F; Bridges SM
PLoS One; 2012; 7(10):e47411. PubMed ID: 23071802
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]