Page 133 - GPD-3-2
P. 133
Gene & Protein in Disease Bioinformatics to identify gene signatures of CF
designing potential peptide vaccine by targeting Shigella doi: 10.1186/1753-6561-3-s4-s10
spp. Serine protease autotransporter subfamily protein siga. 33. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes
J Immunol Res. 2017;2017:6412353.
and genomes. Nucleic Acids Res. 2000;28(1):27-30.
doi: 10.1155/2017/6412353
doi: 10.1093/nar/28.1.27
22. Rahman MR, Islam T, Zaman T, et al. Identification of 34. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M.
molecular signatures and pathways to identify novel KEGG as a reference resource for gene and protein
therapeutic targets in Alzheimer’s disease: Insights annotation. Nucleic Acids Res. 2016;44(D1):D457-D462.
from a systems biomedicine perspective. Genomics.
2020;112(2):1290-1299. doi: 10.1093/nar/gkv1070
doi: 10.1016/j.ygeno.2019.07.018 35. Zhang S, Bodenreider O. Law and order: Assessing and
enforcing compliance with ontological modeling principles
23. Clough E, Barrett T. The gene expression omnibus database.
Methods Mol Biol. 2016;1418:93-110. in the Foundational Model of Anatomy. Comput Biol Med.
2006;36(7-8):674-693.
doi: 10.1007/978-1-4939-3578-9_5
doi: 10.1016/j.compbiomed.2005.04.007
24. Ritchie ME, Phipson B, Wu D, et al. Limma powers 36. Szklarczyk D, Franceschini A, Wyder S, et al. STRING v10:
differential expression analyses for RNA-sequencing and Protein-protein interaction networks, integrated over the
microarray studies. Nucleic Acids Res. 2015;73(7):e47.
tree of life. Nucleic Acids Res. 2015;43(D1):D447-D452.
doi: 10.1093/nar/gkv007
doi: 10.1093/nar/gku1003
25. Benjamini BY, Yekutieli D. The control of the false discovery 37. Shannon P, Markiel A, Ozier O, et al. Cytoscape: A software
rate in multiple testing under dependency. Ann Stat. environment for integrated models of biomolecular
2001;29(4):1165-1188. interaction networks. Genome Res. 2003;13:2498-2504.
26. Aubert J, Bar-Hen A, Daudin JJ, Robin S. Determination of doi: 10.1101/gr.1239303
the differentially expressed genes in microarray experiments
using local FDR. BMC Bioinformatics. 2004;5:125. 38. Hogue CW, Groll M. An automated method for finding
molecular complexes in large protein interaction networks.
doi: 10.1186/1471-2105-5-125 BMC Bioinformatics. 2001;29(1):137-140.
27. Pawitan Y, Michiels S, Koscielny S, Gusnanto A, Ploner A. doi: 10.1093/nar/29.1.137
False discovery rate, sensitivity and sample size for
microarray studies. Bioinformatics. 2005;21(13):3017-3024. 39. Chin CH, Chen SH, Wu HH, Ho CW, Ko MT,
Lin CY. cytoHubba: Identifying hub objects and sub-
doi: 10.1093/bioinformatics/bti448 networks from complex interactome. BMC Syst Biol.
28. Islam MR, Ahmed ML, Kumar Paul B, Bhuiyan T, Ahmed K, 2014;8 Suppl 4(Suppl 4):S11.
Moni MA. Identification of the core ontologies and signature doi: 10.1186/1752-0509-8-S4-S11
genes of polycystic ovary syndrome (PCOS): A bioinformatics
analysis. Informatics Med Unlocked. 2020;18:100304. 40. Wang G. Genome editing for cystic fibrosis. Cells.
2023;12(12):1555.
doi: 10.1016/j.imu.2020.100304
doi: 10.3390/cells12121555
29. Jiao X, Sherman BT, Huang DW, et al. DAVID-WS:
A stateful web service to facilitate gene/protein list analysis. 41. Paterson SL, Barry PJ, Horsley AR. Tezacaftor and ivacaftor
Bioinformatics. 2012;28(13):1805-1806. for the treatment of cystic fibrosis. Expert Rev Respir Med.
2020;14(1):15-30.
doi: 10.1093/bioinformatics/bts251
doi: 10.1080/17476348.2020.1682998
30. Xia J, Gill EE, Hancock REW. NetworkAnalyst for statistical,
visual and network-based meta-analysis of gene expression 42. Kotnala S, Dhasmana A, Kashyap VK, Chauhan SC,
data. Nat Protoc. 2015;10(6):823-844. Yallapu MM, Jaggi M. A bird eye view on cystic fibrosis:
An underestimated multifaceted chronic disorder. Life Sci.
doi: 10.1038/nprot.2015.052 2021;268:118959.
31. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: Tool doi: 10.1016/j.lfs.2020.118959
for the unification of biology. Nat Genet. 2000;25:25-29.
43. O’Neal WK, Knowles MR. Cystic fibrosis disease modifiers:
doi: 10.1038/75556 Complex genetics defines the phenotypic diversity in
a monogenic disease. Annu Rev Genomics Hum Genet.
32. Hulsegge I, Kommadath A, Smits MA. Globaltest and
GOEAST: Two different approaches for Gene Ontology 2018;19:201-222.
analysis. BMC Proc. 2009;3(S4):S10. doi: 10.1146/annurev-genom-083117-021329
Volume 3 Issue 2 (2024) 10 doi: 10.36922/gpd.2937

