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2021 | OriginalPaper | Chapter

4. Simultaneous Clustering of Multiple Gene Expression Datasets for Pattern Discovery

Authors : Basel Abu-Jamous, Asoke K. Nandi

Published in: Advances in Artificial Intelligence, Computation, and Data Science

Publisher: Springer International Publishing

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Background

Healthy cells run sophisticated genetic programmes in order to carry out their various biological processes such as cellular growth, cell division, stress response, and metabolism. The regulation of these genetic programmes is realised at different levels by controlling the production of the required types of large biomolecules such as RNAs, proteins, glycans, and lipids, with different amounts, at different times, and in different sub-cellular locations. Although all cells in an organism, such as skin cells, liver cells, bone cells, and neurons nominally have the same genomic material, they differ in shape and function because of the differences in the genetic programmes that they run.

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Literature
1.
go back to reference Abu-Jamous B, Buffa FM, Harris AL, Nandi AK (2017) In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer. Molec Cancer 16:105 Abu-Jamous B, Buffa FM, Harris AL, Nandi AK (2017) In vitro downregulated hypoxia transcriptome is associated with poor prognosis in breast cancer. Molec Cancer 16:105
2.
go back to reference Abu-Jamous B, Fa R, Nandi AK (2015) Integrative cluster analysis in bioinformatics, 1st edn. Wiley, Pondicherry Abu-Jamous B, Fa R, Nandi AK (2015) Integrative cluster analysis in bioinformatics, 1st edn. Wiley, Pondicherry
3.
go back to reference Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2014) Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome biogenesis. BMC Bioinform 15:322 Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2014) Comprehensive analysis of forty yeast microarray datasets reveals a novel subset of genes (APha-RiB) consistently negatively associated with ribosome biogenesis. BMC Bioinform 15:322
4.
go back to reference Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2015) UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets. BMC Bioinform 16:184 Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2015) UNCLES: method for the identification of genes differentially consistently co-expressed in a specific subset of datasets. BMC Bioinform 16:184
5.
go back to reference Abu-Jamous B, Kelly S (2018) Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data. Genome Biol 19(1):172PubMedPubMedCentral Abu-Jamous B, Kelly S (2018) Clust: automatic extraction of optimal co-expressed gene clusters from gene expression data. Genome Biol 19(1):172PubMedPubMedCentral
6.
go back to reference Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2013) Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery. PLOS One 8(2) Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2013) Paradigm of tunable clustering using binarization of consensus partition matrices (Bi-CoPaM) for gene discovery. PLOS One 8(2)
7.
go back to reference Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2013) Yeast gene CMR1/YDL156W is consistently co-expressed with genes participating in DNA-metabolic processes in a variety of stringent clustering experiments. J Royal Soc Interface 10:20120990 Abu-Jamous B, Fa R, Roberts DJ, Nandi AK (2013) Yeast gene CMR1/YDL156W is consistently co-expressed with genes participating in DNA-metabolic processes in a variety of stringent clustering experiments. J Royal Soc Interface 10:20120990
8.
go back to reference Askautrud HA et al (2014) Global gene expression analysis reveals a link between NDRG1 and vesicle transport. PLoS One 9(1):PubMedPubMedCentral Askautrud HA et al (2014) Global gene expression analysis reveals a link between NDRG1 and vesicle transport. PLoS One 9(1):PubMedPubMedCentral
9.
go back to reference Athar A et al (2019) ArrayExpress update—from bulk to single-cell expression data. Nucleic Acids Res 47(D1):D711–D715PubMed Athar A et al (2019) ArrayExpress update—from bulk to single-cell expression data. Nucleic Acids Res 47(D1):D711–D715PubMed
10.
go back to reference Bazaga A, Leggate D, Weisser H (2020) Genome-wide investigation of gene-cancer associations for the prediction of novel therapeutic targets in oncology. Sci Rep 10:10787PubMedPubMedCentral Bazaga A, Leggate D, Weisser H (2020) Genome-wide investigation of gene-cancer associations for the prediction of novel therapeutic targets in oncology. Sci Rep 10:10787PubMedPubMedCentral
11.
go back to reference Benita Y et al (2009) An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia. Nucleic Acids Res 37(14):4587–4602PubMedPubMedCentral Benita Y et al (2009) An integrative genomics approach identifies Hypoxia Inducible Factor-1 (HIF-1)-target genes that form the core response to hypoxia. Nucleic Acids Res 37(14):4587–4602PubMedPubMedCentral
12.
go back to reference Bester MC, Jacobson D, Bauer FF (2012) Many Saccharomyces cerevisiae cell wall protein encoding genes are coregulated by Mss11, but cellular adhesion phenotypes appear only Flo protein dependent. G3 (Bethesda) 2(1):131–141. Bester MC, Jacobson D, Bauer FF (2012) Many Saccharomyces cerevisiae cell wall protein encoding genes are coregulated by Mss11, but cellular adhesion phenotypes appear only Flo protein dependent. G3 (Bethesda) 2(1):131–141.
13.
go back to reference Boer CGD, Hughes TR (2011) YeTFaSCo: a database of evaluated yeast transcription factor sequence specificities. Nucl Acids Res 40(D1):D169–D179 Boer CGD, Hughes TR (2011) YeTFaSCo: a database of evaluated yeast transcription factor sequence specificities. Nucl Acids Res 40(D1):D169–D179
14.
go back to reference Bosio MC, Negri R, Dieci G (2011) Promoter architectures in the yeast ribosomal expression program. Transcription 2(2):71–77PubMedPubMedCentral Bosio MC, Negri R, Dieci G (2011) Promoter architectures in the yeast ribosomal expression program. Transcription 2(2):71–77PubMedPubMedCentral
15.
go back to reference Buffa FM et al (2011) microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Can Res 71(17):5635 Buffa FM et al (2011) microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Can Res 71(17):5635
16.
go back to reference Buffa FM, Harris AL, West CM, Miller CJ (2010) Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene. Br J Cancer 102:428–435PubMedPubMedCentral Buffa FM, Harris AL, West CM, Miller CJ (2010) Large meta-analysis of multiple cancers reveals a common, compact and highly prognostic hypoxia metagene. Br J Cancer 102:428–435PubMedPubMedCentral
17.
go back to reference Cabassi A, Kirk PDW (2020) Multiple kernel learning for integrative consensus clustering of omic datasets. Bioinformatics (In press) Cabassi A, Kirk PDW (2020) Multiple kernel learning for integrative consensus clustering of omic datasets. Bioinformatics (In press)
18.
go back to reference Camps C et al (2014) Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia. Molec Cancer 13:28 Camps C et al (2014) Integrated analysis of microRNA and mRNA expression and association with HIF binding reveals the complexity of microRNA expression regulation under hypoxia. Molec Cancer 13:28
19.
go back to reference Chaudhary K, Poirion OB, Lu L, Garmire LX (2018) Deep learning-based multi-omics integration robustly predicts survival in liver cancer. Clin Cancer Res 24(6):1248–1259PubMed Chaudhary K, Poirion OB, Lu L, Garmire LX (2018) Deep learning-based multi-omics integration robustly predicts survival in liver cancer. Clin Cancer Res 24(6):1248–1259PubMed
20.
go back to reference Cheerla A, Gevaert O (2019) Deep learning with multimodal representation for pancancer prognosis prediction. Bioinformatics 35:i446–i454PubMedPubMedCentral Cheerla A, Gevaert O (2019) Deep learning with multimodal representation for pancancer prognosis prediction. Bioinformatics 35:i446–i454PubMedPubMedCentral
21.
go back to reference Chen EY et al (2013) Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinform 14:128 Chen EY et al (2013) Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinform 14:128
22.
go back to reference Chen X et al (2014) XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway. Nature 508(7494):103–107PubMedPubMedCentral Chen X et al (2014) XBP1 promotes triple-negative breast cancer by controlling the HIF1α pathway. Nature 508(7494):103–107PubMedPubMedCentral
23.
go back to reference Chin SL, Marcus IM, Klevecz RR, Li CM (2012) Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators. FEBS J 279(6):1119–1130PubMedPubMedCentral Chin SL, Marcus IM, Klevecz RR, Li CM (2012) Dynamics of oscillatory phenotypes in Saccharomyces cerevisiae reveal a network of genome-wide transcriptional oscillators. FEBS J 279(6):1119–1130PubMedPubMedCentral
24.
go back to reference Chumnanpuen P, Nookaew I, Nielsen J (2013) Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (INO2 and INO4) on lipid metabolism in yeast. BMC Syst Biol 7(Suppl 3):S7PubMedPubMedCentral Chumnanpuen P, Nookaew I, Nielsen J (2013) Integrated analysis, transcriptome-lipidome, reveals the effects of INO-level (INO2 and INO4) on lipid metabolism in yeast. BMC Syst Biol 7(Suppl 3):S7PubMedPubMedCentral
25.
26.
go back to reference Curtis C et al (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486:346–352PubMedPubMedCentral Curtis C et al (2012) The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 486:346–352PubMedPubMedCentral
27.
go back to reference Danila FR et al (2018) Multiple mechanisms for enhanced plasmodesmata density in disparate subtypes of C4 grasses. J Exp Bot 69(5):1135–1145PubMedPubMedCentral Danila FR et al (2018) Multiple mechanisms for enhanced plasmodesmata density in disparate subtypes of C4 grasses. J Exp Bot 69(5):1135–1145PubMedPubMedCentral
28.
go back to reference Dikicioglu D et al (2011) How yeast re-programmes its transcriptional profile in response to different nutrient impulses. BMC Syst Biol 5:148, 163 Dikicioglu D et al (2011) How yeast re-programmes its transcriptional profile in response to different nutrient impulses. BMC Syst Biol 5:148, 163
29.
go back to reference Drobna E et al (2012) Overexpression of the YAP1, PDE2, and STB3 genes enhances the tolerance of yeast to oxidative stress induced by 7-chlorotetrazolo[5,1-c]benzo[1,2,4]triazine. FEMS Yeast Res 12:958–968PubMed Drobna E et al (2012) Overexpression of the YAP1, PDE2, and STB3 genes enhances the tolerance of yeast to oxidative stress induced by 7-chlorotetrazolo[5,1-c]benzo[1,2,4]triazine. FEMS Yeast Res 12:958–968PubMed
30.
go back to reference Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucl Acids Res 30(1):207–210PubMedPubMedCentral Edgar R, Domrachev M, Lash AE (2002) Gene expression omnibus: NCBI gene expression and hybridization array data repository. Nucl Acids Res 30(1):207–210PubMedPubMedCentral
31.
go back to reference Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. PNAS 95(25):14863–14868PubMedPubMedCentral Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. PNAS 95(25):14863–14868PubMedPubMedCentral
32.
go back to reference Elvidge GP et al (2006) Concordant regulation of gene expression by hypoxia and 2-oxoglutarate-dependent dioxygenase inhibition: the role of HIF-1alpha, HIF-2alpha, and other pathways. J Biol Chem 281(22):15215–15226PubMed Elvidge GP et al (2006) Concordant regulation of gene expression by hypoxia and 2-oxoglutarate-dependent dioxygenase inhibition: the role of HIF-1alpha, HIF-2alpha, and other pathways. J Biol Chem 281(22):15215–15226PubMed
33.
go back to reference Emms DM, Kelly S (2015) OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol 16:157PubMedPubMedCentral Emms DM, Kelly S (2015) OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol 16:157PubMedPubMedCentral
34.
go back to reference Enright AJ, Van Dongen S, Ouzounis CA (2002) An efficient algorithm for large-scale detection of protein families. Nucl Acids Res 30(7):1575–1584PubMedPubMedCentral Enright AJ, Van Dongen S, Ouzounis CA (2002) An efficient algorithm for large-scale detection of protein families. Nucl Acids Res 30(7):1575–1584PubMedPubMedCentral
35.
go back to reference Ferreira RT et al (2012) Arsenic stress elicits cytosolic Ca(2+) bursts and Crz1 activation in Saccharomyces cerevisiae. Microbiology 158(Pt 9):2293–2302PubMed Ferreira RT et al (2012) Arsenic stress elicits cytosolic Ca(2+) bursts and Crz1 activation in Saccharomyces cerevisiae. Microbiology 158(Pt 9):2293–2302PubMed
36.
go back to reference Foo M et al (2018) A framework for engineering stress resilient plants using genetic feedback control and regulatory network rewiring. ACS Synth Biol 7(6):1553–1564PubMed Foo M et al (2018) A framework for engineering stress resilient plants using genetic feedback control and regulatory network rewiring. ACS Synth Biol 7(6):1553–1564PubMed
37.
go back to reference Ge H et al (2010) Comparative analyses of time-course gene expression profiles of the long-lived sch9Delta mutant. Nucl Acids Res 38(1):143–158PubMed Ge H et al (2010) Comparative analyses of time-course gene expression profiles of the long-lived sch9Delta mutant. Nucl Acids Res 38(1):143–158PubMed
38.
go back to reference González-Aguilera C et al (2011) Nab2 functions in the metabolism of RNA driven by polymerases II and III. Mol Biol Cell 22(15):2729–2740PubMedPubMedCentral González-Aguilera C et al (2011) Nab2 functions in the metabolism of RNA driven by polymerases II and III. Mol Biol Cell 22(15):2729–2740PubMedPubMedCentral
39.
go back to reference Gosset G (2017) Engineering of microorganisms for the production of chemicals and biofuels from renewable resources, 1st edn. Springer International Publishing, Cham Gosset G (2017) Engineering of microorganisms for the production of chemicals and biofuels from renewable resources, 1st edn. Springer International Publishing, Cham
40.
go back to reference Harris AL (2002) Hypoxia—a key regulatory factor in tumour growth. Nat Rev Cancer 2:38–47PubMed Harris AL (2002) Hypoxia—a key regulatory factor in tumour growth. Nat Rev Cancer 2:38–47PubMed
41.
go back to reference Harris B, Barberis A, West C, Buffa F (2015) Gene expression signatures as biomarkers of tumour hypoxia. Clin Oncol 27(10):547–560 Harris B, Barberis A, West C, Buffa F (2015) Gene expression signatures as biomarkers of tumour hypoxia. Clin Oncol 27(10):547–560
42.
go back to reference Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43(1):59–69 Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43(1):59–69
43.
go back to reference Koritzinsky M et al (2013) Two phases of disulfide bond formation have differing requirements for oxygen. J Cell Biol (JCB) 203(4):615–627PubMed Koritzinsky M et al (2013) Two phases of disulfide bond formation have differing requirements for oxygen. J Cell Biol (JCB) 203(4):615–627PubMed
44.
go back to reference Kovacs LAS et al (2012) Cyclin-dependent kinases are regulators and effectors of oscillations driven by a transcription factor network. Mol Cell 45(5):669–679PubMedCentral Kovacs LAS et al (2012) Cyclin-dependent kinases are regulators and effectors of oscillations driven by a transcription factor network. Mol Cell 45(5):669–679PubMedCentral
45.
go back to reference Krutilina R et al (2014) MicroRNA-18a inhibits hypoxia-inducible factor 1α activity and lung metastasis in basal breast cancers. Breast Cancer Res 16:R78PubMedPubMedCentral Krutilina R et al (2014) MicroRNA-18a inhibits hypoxia-inducible factor 1α activity and lung metastasis in basal breast cancers. Breast Cancer Res 16:R78PubMedPubMedCentral
46.
go back to reference Kuleshov MV et al (2016) Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucl Acids Res 44(W1):W90–W97PubMedPubMedCentral Kuleshov MV et al (2016) Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucl Acids Res 44(W1):W90–W97PubMedPubMedCentral
47.
go back to reference Lai L-C et al (2011) Down-regulation of NDRG1 promotes migration of cancer cells during reoxygenation. PLoS One 6(8):e24375PubMedPubMedCentral Lai L-C et al (2011) Down-regulation of NDRG1 promotes migration of cancer cells during reoxygenation. PLoS One 6(8):e24375PubMedPubMedCentral
48.
go back to reference Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559 Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559
49.
go back to reference Lanza AM, Blazeck JJ, Crook NC, Alper HS (2012) Linking yeast Gcn5p catalytic function and gene regulation using a quantitative, graded dominant mutant approach. PLoS One 7(4):e36193PubMedPubMedCentral Lanza AM, Blazeck JJ, Crook NC, Alper HS (2012) Linking yeast Gcn5p catalytic function and gene regulation using a quantitative, graded dominant mutant approach. PLoS One 7(4):e36193PubMedPubMedCentral
50.
go back to reference Larsson M et al (2013) Functional studies of the yeast med5, med15 and med16 mediator tail subunits. PLoS One 8(8):e73137PubMedPubMedCentral Larsson M et al (2013) Functional studies of the yeast med5, med15 and med16 mediator tail subunits. PLoS One 8(8):e73137PubMedPubMedCentral
51.
52.
go back to reference Liu Z et al (2013) Anaerobic α-amylase production and secretion with fumarate as the final electron acceptor in Saccharomyces cerevisiae. Appl Environ Microbiol 79(9):2962–2967PubMedPubMedCentral Liu Z et al (2013) Anaerobic α-amylase production and secretion with fumarate as the final electron acceptor in Saccharomyces cerevisiae. Appl Environ Microbiol 79(9):2962–2967PubMedPubMedCentral
53.
go back to reference Lu X et al (2010) In vivo dynamics and distinct functions of hypoxia in primary tumor growth and organotropic metastasis of breast cancer. Can Res 70(10):3905–3914 Lu X et al (2010) In vivo dynamics and distinct functions of hypoxia in primary tumor growth and organotropic metastasis of breast cancer. Can Res 70(10):3905–3914
54.
go back to reference MacQueen J (1967) Some methods for classification and analysis of multivariate observations. University of California Press, pp 281–297 MacQueen J (1967) Some methods for classification and analysis of multivariate observations. University of California Press, pp 281–297
55.
go back to reference Matia-González AM, Rodríguez-Gabriel MA (2011) Slt2 MAPK pathway is essential for cell integrity in the presence of arsenate. Yeast 28(1):9–17PubMed Matia-González AM, Rodríguez-Gabriel MA (2011) Slt2 MAPK pathway is essential for cell integrity in the presence of arsenate. Yeast 28(1):9–17PubMed
56.
go back to reference Miller LD et al (2005) An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. PNAS 102(38):13550–13555PubMedPubMedCentral Miller LD et al (2005) An expression signature for p53 status in human breast cancer predicts mutation status, transcriptional effects, and patient survival. PNAS 102(38):13550–13555PubMedPubMedCentral
57.
go back to reference Mole DR et al (2009) Genome-wide association of hypoxia-inducible factor (HIF)-1alpha and HIF-2alpha DNA binding with expression profiling of hypoxia-inducible transcripts. J Biol Chem 284:16767–16775PubMedPubMedCentral Mole DR et al (2009) Genome-wide association of hypoxia-inducible factor (HIF)-1alpha and HIF-2alpha DNA binding with expression profiling of hypoxia-inducible transcripts. J Biol Chem 284:16767–16775PubMedPubMedCentral
58.
go back to reference Morillo-Huesca M, Clemente-Ruiz M, Andújar E, Prado F (2010) The SWR1 histone replacement complex causes genetic instability and genome-wide transcription misregulation in the absence of H2A.Z. PLOS One 5(8):e12143 Morillo-Huesca M, Clemente-Ruiz M, Andújar E, Prado F (2010) The SWR1 histone replacement complex causes genetic instability and genome-wide transcription misregulation in the absence of H2A.Z. PLOS One 5(8):e12143
59.
go back to reference Nguyen PA et al (2019) Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects. Nat Commun 10:1579PubMedPubMedCentral Nguyen PA et al (2019) Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects. Nat Commun 10:1579PubMedPubMedCentral
60.
go back to reference Orlando DA et al (2008) Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature 453:944–947PubMedPubMedCentral Orlando DA et al (2008) Global control of cell-cycle transcription by coupled CDK and network oscillators. Nature 453:944–947PubMedPubMedCentral
61.
go back to reference Ortiz-Barahona A et al (2010) Genome-wide identification of hypoxia-inducible factor binding sites and target genes by a probabilistic model integrating transcription-profiling data and in silico binding site prediction. Nucl Acids Res 38(7):2332–2345PubMedPubMedCentral Ortiz-Barahona A et al (2010) Genome-wide identification of hypoxia-inducible factor binding sites and target genes by a probabilistic model integrating transcription-profiling data and in silico binding site prediction. Nucl Acids Res 38(7):2332–2345PubMedPubMedCentral
62.
go back to reference Paraskevopoulou S, Dennis AB, Weithoff G, Tiedemann R (2020) Temperature-dependent life history and transcriptomic responses in heat-tolerant versus heat-sensitive Brachionus rotifers. Sci Rep 10:13281PubMedPubMedCentral Paraskevopoulou S, Dennis AB, Weithoff G, Tiedemann R (2020) Temperature-dependent life history and transcriptomic responses in heat-tolerant versus heat-sensitive Brachionus rotifers. Sci Rep 10:13281PubMedPubMedCentral
63.
go back to reference Parreiras LS, Kohn LM, Anderson JB (2011) Cellular effects and epistasis among three determinants of adaptation in experimental populations of Saccharomyces cerevisiae. Eukaryot Cell 10(10):1348–1356PubMedPubMedCentral Parreiras LS, Kohn LM, Anderson JB (2011) Cellular effects and epistasis among three determinants of adaptation in experimental populations of Saccharomyces cerevisiae. Eukaryot Cell 10(10):1348–1356PubMedPubMedCentral
64.
go back to reference Sanz AB et al (2012) Chromatin remodeling by the SWI/SNF complex is essential for transcription mediated by the yeast cell wall integrity MAPK pathway. Mol Biol Cell 23(14):2805–2817PubMed Sanz AB et al (2012) Chromatin remodeling by the SWI/SNF complex is essential for transcription mediated by the yeast cell wall integrity MAPK pathway. Mol Biol Cell 23(14):2805–2817PubMed
65.
go back to reference Schneider P et al (2020) Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discovery 19:353–364PubMed Schneider P et al (2020) Rethinking drug design in the artificial intelligence era. Nat Rev Drug Discovery 19:353–364PubMed
66.
go back to reference Schödel J et al (2011) High-resolution genome-wide mapping of HIF-binding sites by ChIP-seq. Blood 117(23):e207–e217PubMedPubMedCentral Schödel J et al (2011) High-resolution genome-wide mapping of HIF-binding sites by ChIP-seq. Blood 117(23):e207–e217PubMedPubMedCentral
67.
go back to reference Semenza GL (2014) Oxygen sensing, hypoxia-inducible factors, and disease pathophysiology. Ann Rev Pathol 9:47–71 Semenza GL (2014) Oxygen sensing, hypoxia-inducible factors, and disease pathophysiology. Ann Rev Pathol 9:47–71
68.
go back to reference Shen C, Kaelin WGJ (2013) The VHL/HIF axis in clear cell renal carcinoma. Semin Cancer Biol 23(1):18–25PubMed Shen C, Kaelin WGJ (2013) The VHL/HIF axis in clear cell renal carcinoma. Semin Cancer Biol 23(1):18–25PubMed
69.
go back to reference Strassburg K et al (2010) Dynamic transcriptional and metabolic responses in yeast adapting to temperature stress. OMICS 14(3):249–259PubMedPubMedCentral Strassburg K et al (2010) Dynamic transcriptional and metabolic responses in yeast adapting to temperature stress. OMICS 14(3):249–259PubMedPubMedCentral
70.
go back to reference Suzuki T, Iwahashi Y (2011) Gene expression profiles of yeast Saccharomyces cerevisiae sod1 caused by patulin toxicity and evaluation of recovery potential of ascorbic acid. J Agric Food Chem 59(13):7145–7154PubMed Suzuki T, Iwahashi Y (2011) Gene expression profiles of yeast Saccharomyces cerevisiae sod1 caused by patulin toxicity and evaluation of recovery potential of ascorbic acid. J Agric Food Chem 59(13):7145–7154PubMed
71.
go back to reference Suzuki T, Iwahashi Y (2012) Comprehensive gene expression analysis of type B trichothecenes. J Agric Food Chem 60(37):9519–9527PubMed Suzuki T, Iwahashi Y (2012) Comprehensive gene expression analysis of type B trichothecenes. J Agric Food Chem 60(37):9519–9527PubMed
72.
go back to reference Tang X et al (2012) Functional interaction between responses to lactic acidosis and hypoxia regulates genomic transcriptional outputs. Can Res 72(2):491–502 Tang X et al (2012) Functional interaction between responses to lactic acidosis and hypoxia regulates genomic transcriptional outputs. Can Res 72(2):491–502
73.
go back to reference Tellaroli P et al (2016) Cross-clustering: A partial clustering algorithm with automatic estimation of the number of clusters. PLoS One 11(3):PubMedPubMedCentral Tellaroli P et al (2016) Cross-clustering: A partial clustering algorithm with automatic estimation of the number of clusters. PLoS One 11(3):PubMedPubMedCentral
74.
go back to reference The Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumors. Nature 490(7418):61–70PubMedCentral The Cancer Genome Atlas Network (2012) Comprehensive molecular portraits of human breast tumors. Nature 490(7418):61–70PubMedCentral
75.
go back to reference Wade SL, Poorey K, Bekiranov S, Auble DT (2009) The Snf1 kinase and proteasome-associated Rad23 regulate UV-responsive gene expression. EMBO J 28(19):2919–2931PubMedPubMedCentral Wade SL, Poorey K, Bekiranov S, Auble DT (2009) The Snf1 kinase and proteasome-associated Rad23 regulate UV-responsive gene expression. EMBO J 28(19):2919–2931PubMedPubMedCentral
76.
go back to reference Wang Y et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679PubMed Wang Y et al (2005) Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679PubMed
77.
go back to reference Xia X, Kung AL (2009) Preferential binding of HIF-1 to transcriptionally active loci determines cell-type specific response to hypoxia. Genome Biol 10:R113PubMedPubMedCentral Xia X, Kung AL (2009) Preferential binding of HIF-1 to transcriptionally active loci determines cell-type specific response to hypoxia. Genome Biol 10:R113PubMedPubMedCentral
78.
go back to reference Xue-Franzén Y, Henriksson J, Bürglin TR, Wright AP (2013) Distinct roles of the Gcn5 histone acetyltransferase revealed during transient stress-induced reprogramming of the genome. BMC Genom 14:479 Xue-Franzén Y, Henriksson J, Bürglin TR, Wright AP (2013) Distinct roles of the Gcn5 histone acetyltransferase revealed during transient stress-induced reprogramming of the genome. BMC Genom 14:479
79.
go back to reference Yang J et al (2010) The histone demethylase JMJD2B is regulated by estrogen receptor alpha and hypoxia, and is a key mediator of estrogen induced growth. Can Res 70(16):6456–6466 Yang J et al (2010) The histone demethylase JMJD2B is regulated by estrogen receptor alpha and hypoxia, and is a key mediator of estrogen induced growth. Can Res 70(16):6456–6466
Metadata
Title
Simultaneous Clustering of Multiple Gene Expression Datasets for Pattern Discovery
Authors
Basel Abu-Jamous
Asoke K. Nandi
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-69951-2_4

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