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Items: 1 to 20 of 29

1.

Multi-Objective Optimized Fuzzy Clustering for Detecting Cell Clusters from Single-Cell Expression Profiles.

Mallik S, Zhao Z.

Genes (Basel). 2019 Aug 13;10(8). pii: E611. doi: 10.3390/genes10080611.

2.
3.

Identification of gene signatures from RNA-seq data using Pareto-optimal cluster algorithm.

Mallik S, Zhao Z.

BMC Syst Biol. 2018 Dec 21;12(Suppl 8):126. doi: 10.1186/s12918-018-0650-2.

4.

An evaluation of supervised methods for identifying differentially methylated regions in Illumina methylation arrays.

Mallik S, Odom GJ, Gao Z, Gomez L, Chen X, Wang L.

Brief Bioinform. 2018 Sep 17. doi: 10.1093/bib/bby085. [Epub ahead of print]

PMID:
30239597
6.

WeCoMXP: Weighted Connectivity Measure Integrating Co-Methylation, Co-Expression and Protein-Protein Interactions for Gene-Module Detection.

Mallik S, Bandyopadhyay S.

IEEE/ACM Trans Comput Biol Bioinform. 2018 Sep 3. doi: 10.1109/TCBB.2018.2868348. [Epub ahead of print]

PMID:
30183644
7.

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. doi: 10.1109/TNB.2018.2803021.

PMID:
29870335
8.

Topology and Oligomerization of Mono- and Oligomeric Proteins Regulate Their Half-Lives in the Cell.

Mallik S, Kundu S.

Structure. 2018 Jun 5;26(6):869-878.e3. doi: 10.1016/j.str.2018.04.015. Epub 2018 May 24.

9.

Translational regulation of ribosomal protein S15 drives characteristic patterns of protein-mRNA epistasis.

Mallik S, Basu S, Hait S, Kundu S.

Proteins. 2018 Aug;86(8):827-832. doi: 10.1002/prot.25518. Epub 2018 May 6.

PMID:
29679401
10.

Detecting TF-miRNA-gene network based modules for 5hmC and 5mC brain samples: a intra- and inter-species case-study between human and rhesus.

Maulik U, Sen S, Mallik S, Bandyopadhyay S.

BMC Genet. 2018 Jan 22;19(1):9. doi: 10.1186/s12863-017-0574-7.

11.
12.

Transiently disordered tails accelerate folding of globular proteins.

Mallik S, Ray T, Kundu S.

FEBS Lett. 2017 Jul;591(14):2180-2191. doi: 10.1002/1873-3468.12725. Epub 2017 Jul 8.

13.

Coevolutionary constraints in the sequence-space of macromolecular complexes reflect their self-assembly pathways.

Mallik S, Kundu S.

Proteins. 2017 Jul;85(7):1183-1189. doi: 10.1002/prot.25292. Epub 2017 Apr 6.

PMID:
28342228
14.
15.

Integrating Multiple Data Sources for Combinatorial Marker Discovery: A Study in Tumorigenesis.

Bandyopadhyay S, Mallik S.

IEEE/ACM Trans Comput Biol Bioinform. 2018 Mar-Apr;15(2):673-687. doi: 10.1109/TCBB.2016.2636207. Epub 2016 Dec 6.

PMID:
28114033
16.

Identifying Epigenetic Biomarkers using Maximal Relevance and Minimal Redundancy Based Feature Selection for Multi-Omics Data.

Mallik S, Bhadra T, Maulik U.

IEEE Trans Nanobioscience. 2017 Jan;16(1):3-10. doi: 10.1109/TNB.2017.2650217. Epub 2017 Jan 9.

PMID:
28092570
17.

IDPT: Insights into potential intrinsically disordered proteins through transcriptomic analysis of genes for prostate carcinoma epigenetic data.

Mallik S, Sen S, Maulik U.

Gene. 2016 Jul 15;586(1):87-96. doi: 10.1016/j.gene.2016.03.056. Epub 2016 Apr 7.

PMID:
27060408
18.

Predicting protein folding rate change upon point mutation using residue-level coevolutionary information.

Mallik S, Das S, Kundu S.

Proteins. 2016 Jan;84(1):3-8. doi: 10.1002/prot.24960. Epub 2015 Dec 9.

PMID:
26566752
19.

MiRNA-TF-gene network analysis through ranking of biomolecules for multi-informative uterine leiomyoma dataset.

Mallik S, Maulik U.

J Biomed Inform. 2015 Oct;57:308-19. doi: 10.1016/j.jbi.2015.08.014. Epub 2015 Aug 19.

20.

Co-evolutionary constraints of globular proteins correlate with their folding rates.

Mallik S, Kundu S.

FEBS Lett. 2015 Aug 4;589(17):2179-85. doi: 10.1016/j.febslet.2015.06.032. Epub 2015 Jul 8.

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