[65] Kharb S, Joshi A. Editorial: eDiagnostics and monitoring for precision endocrinology Front Endocrinol. 2023 Jul 4;14:1229475. doi: 10.3389/fendo.2023
[64] Zelco A, Wapeesittipan P, Joshi A. Insights into Sex and Gender Differences in Brain and Psychopathologies Using Big Data. Life 2023 Aug 2;13(8):1676. doi: 10.3390/life13081676.
[63] Wapeesittipan, P., & Joshi, A. (2023) Integrated analysis of robust sex-biased gene signatures in human brain. Biol Sex Differ. 2023 May 24;14(1):36. doi: 10.1186/s13293-023-00515-w.
[62] Kharb, S. & Joshi, A. Multi-omics and machine learning for the prevention and management of female reproductive health. Front. Endocrinol. Feb 23;14:1081667. doi: 10.3389/fendo.2023.1081667.
[61] Sarkar I, Davies R, Aarebrot AK, Solberg SM, Petrovic A, Joshi AM, Bergum B, Brun JG, Hammenfors D, Jonsson R, Appel S. Aberrant signaling of immune cells in Sjögren’s syndrome patient subgroups upon interferon stimulation. Front Immunol. 2022 Aug 22;13:854183. doi: 10.3389/fimmu.2022.854183.
[60] Mantsoki A, Parussel K, Joshi A. Identification and Characterisation of Putative Enhancer Elements in Mouse Embryonic Stem Cells. Bioinform Biol Insights. 2021 Feb 9;15:1177932220974623.
[59] Grapotte, M., Saraswat, M., Bessière, C. et al. Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network. Nat Commun 12, 297 (2021).
[58] Devailly G, Joshi A Comprehensive analysis of epigenetic signatures of human transcription control Mol. Omics, 2021, 17, 692-705 DOI: 10.1039/D0MO00130A
[57] Joshi , A. and Romanowska , J. ( 2020 ). Recent advances in computational-based approaches in epigenetics studies. In Epigenetics Methods, vol. 18, ed. T. Tollefsbol , 569 – 590 . San Diego, CA : Elsevier .
[56] Meek S, Wei J, Oh T, Watson T, Olavarrieta J, Sutherland L, Carlson DF, Salzano A, Chandra T, Joshi A, Burdon T. A Stem Cell Reporter for Investigating Pluripotency and Self-Renewal in the Rat. Stem Cell Reports. 2020 Jan 14;14(1):154-166.
[55] Romanowska J, Joshi A. From Genotype to Phenotype: Through Chromatin. Genes. 2019 Jan 23;10(2). pii: E76. doi: 10.3390/genes10020076.
[54] Vipin D, Wang L, Devailly G, Michoel T, Joshi A. Causal Transcription Regulatory Network Inference Using Enhancer Activity as a Causal Anchor. International Journal of Molecular Science 2018 Nov 15;19(11). doi: 10.3390/ijms19113609.
[53] Devailly G, Joshi A. Insights into mammalian transcription control by systematic analysis of ChIP sequencing data. BMC Bioinformatics 2018 Nov 20;1:409. doi: 10.1186/s12859-018-2377-x.
[52] Mantsoki A, Devailly G, Joshi A. Dynamics of promoter bivalency and RNAP II pausing in mouse stem and differentiated cells. BMC Developmental Biology, 18(1):2 (2018). ISSN 1471-213X. doi: 10.1186/s12861-018-0163-7.
[51] Arzalluz-Luque Ã, Devailly G, Mantsoki A, Joshi A. Delineating biological and technical variance in single cell expression data. The International Journal of Biochemistry & Cell Biology, 90:161–166 (2017). ISSN 1878-5875. doi:10.1016/j.biocel.2017.07.006.
[50] Giotti B, Joshi A, Freeman TC. Meta-analysis reveals conserved cell cycle transcriptional network across multiple human cell types. BMC Genomics, 18(1):30 (2017). ISSN 1471-2164. doi:10.1186/s12864-016- 3435-2.
[49] Reyes PFL, Michoel T, Joshi A, Devailly G. Meta-analysis of Liver and Heart Transcriptomic Data for Functional Annotation Transfer in Mammalian Orthologs. Computational and Structural Biotechnology Journal, 15:425–432 (2017). ISSN 2001-0370. doi:10.1016/j.csbj.2017.08.002.
[48] Sugiyama D, Joshi A, Kulkeaw K, Tan KS, Yokoo-Inoue T, Mizuochi-Yanagi C, Yasuda K, Doi A, Iino T, Itoh M, Nagao-Sato S, Tani K, Akashi K, Hayashizaki Y, Suzuki H, Kawaji H, Carninci P, Forrest ARR. A Transcriptional Switch Point During Hematopoietic Stem and Progenitor Cell Ontogeny. Stem Cells and Development, 26(5):314–327 (2017). ISSN 1557-8534. doi:10.1089/scd.2016.0194.
[47] Bain CC, Hawley CA, Garner H, Scott CL, Schridde A, Steers NJ, Mack M, Joshi A, Guilliams M, Mowat AMI, Geissmann F, Jenkins SJ. Long-lived self-renewing bone marrow-derived macrophages displace embryo-derived cells to inhabit adult serous cavities. Nature Communications, 7:ncomms11852 (2016). ISSN 2041-1723. doi:10.1038/ncomms11852.
[46] Banks CJ, Joshi A, Michoel T. Functional transcription factor target discovery via compendia of binding and expression profiles. Scientific Reports, 6:20649 (2016). ISSN 2045-2322. doi:10.1038/srep20649.
[45] Devailly G, Mantsoki A, Joshi A. Heat*seq: an interactive web tool for high-throughput sequencing experiment comparison with public data. Bioinformatics, 32(21):3354–3356 (2016). ISSN 1367-4811. doi:10.1093/bioinformatics/btw407.
[44] Mantsoki A, Devailly G, Joshi A. Corrigendum: CpG island erosion, polycomb occupancy and sequence motif enrichment at bivalent promoters in mammalian embryonic stem cells. Scientific Reports, 6:25682 (2016). ISSN 2045-2322. doi:10.1038/srep25682.
[43] Mantsoki A, Devailly G, Joshi A. Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data. Computational Biology and Chemistry, 63:52–61 (2016). ISSN 1476-928X. doi:10.1016/j.compbiolchem.2016.02.004.
[42] Berry RL, Ozdemir DD, Aronow B, Lindstrà ̋um NO, Dudnakova T, Thornburn A, Perry P, Baldock R, Armit C, Joshi A, Jeanpierre C, Shan J, Vainio S, Baily J, Brownstein D, Davies J, Hastie ND, Hohenstein P. Deducing the stage of origin of Wilms’ tumours from a developmental series of Wt1-mutant mice. Disease Models & Mechanisms, 8(8):903–917 (2015). ISSN 1754-8411. doi:10.1242/dmm.018523.
[41] Carbajo D, Magi S, Itoh M, Kawaji H, Lassmann T, Arner E, Forrest ARR, Carninci P, Hayashizaki Y, Daub CO, FANTOM consortium, Okada-Hatakeyama M, Mar JC. Application of Gene Expression Trajectories Initiated from ErbB Receptor Activation Highlights the Dynamics of Divergent Promoter Usage. PloS One, 10(12):e0144176 (2015). ISSN 1932-6203. doi:10.1371/journal.pone.0144176.
[40] Devailly G, Mantsoki A, Michoel T, Joshi A. Variable reproducibility in genome-scale public data: A case study using ENCODE ChIP sequencing resource. FEBS letters, 589(24 Pt B):3866–3870 (2015). ISSN 1873-3468. doi:10.1016/j.febslet.2015.11.027.1
[39] Hurst LD, Ghanbarian AT, Forrest ARR, FANTOM consortium, Huminiecki L. The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome. PLoS Biology, 13(12):e1002315 (2015). ISSN 1545-7885. doi:10.1371/journal.pbio.1002315.
[38] Liang C, FANTOM Consortium, Forrest ARR, Wagner GP. The statistical geometry of transcriptome divergence in cell-type evolution and cancer. Nature Communications, 6:6066 (2015). ISSN 2041-1723. doi:10.1038/ncomms7066.
[37] Mantsoki A, Devailly G, Joshi A. CpG island erosion, polycomb occupancy and sequence motif enrichment at bivalent promoters in mammalian embryonic stem cells. Scientific Reports, 5:16791 (2015). ISSN 2045-2322. doi:10.1038/srep16791.
[36] Joshi A, Beck Y, Michoel T. Multi-species network inference improves gene regulatory network reconstruction for early embryonic development in Drosophila. Journal of Computational Biology, 22(4):253–265 (2015). ISSN 1557-8666. doi: 10.1089/cmb.2014.0290.
[35] Joshi A, Pooley C, Freeman TC, Lennartsson A, Babina M, Schmidl C, Geijtenbeek T, FANTOM Consortium, Michoel T, Severin J, Itoh M, Lassmann T, Kawaji H, Hayashizaki Y, Carninci P, Forrest ARR, Rehli M, Hume DA. Technical Advance: Transcription factor, promoter, and enhancer utilization in human myeloid cells. Journal of Leukocyte Biology, 97(5):985–995 (2015). ISSN 1938-3673. doi: 10.1189/jlb.6TA1014-477RR.
[34] Yoshihara M, Ohmiya H, Hara S, Kawasaki S, FANTOM consortium, Hayashizaki Y, Itoh M, Kawaji H, Tsujikawa M, Nishida K. Discovery of molecular markers to discriminate corneal endothelial cells in the human body. PloS One, 10(3):e0117581 (2015). ISSN 1932-6203. doi:10.1371/journal.pone.0117581.
[33] Andersson R, Gebhard C, Miguel-Escalada I, Hoof I, Bornholdt J, Boyd M, Chen Y, Zhao X, Schmidl C, .. Joshi A, .. Suzuki H, Hayashizaki Y, MÃijller F, Forrest ARR, Carninci P, Rehli M, Sandelin A. An atlas of active enhancers across human cell types and tissues. Nature, 507(7493):455–461 (2014). ISSN 1476-4687. doi:10.1038/nature12787.
[32] Arner E, Forrest ARR, Ehrlund A, Mejhert N, Itoh M, Kawaji H, Lassmann T, Laurencikiene J, .., Arner P, FANTOM Consortium. Ceruloplasmin is a novel adipokine which is overexpressed in adipose tissue of obese subjects and in obesity-associated cancer cells. PloS One, 9(3):e80274 (2014). ISSN 1932-6203. doi:10.1371/journal.pone.0080274.
[31] FANTOM Consortium and the RIKEN PMI and CLST (DGT), Forrest ARR, Kawaji H, Rehli M, Baillie JK, .., Jia H, Joshi A, Jurman G, .., Freeman TC, Lenhard B, Bajic VB, Taylor MS, Makeev VJ, Sandelin A, Hume DA, Carninci P, Hayashizaki Y. A promoter-level mammalian expression atlas. Nature, 507(7493):462–470 (2014). ISSN 1476-4687. doi:10.1038/nature13182.
[30] Hasegawa Y, Tang D, Takahashi N, Hayashizaki Y, Forrest ARR, FANTOM Consortium, Suzuki H. CCL2 enhances pluripotency of human induced pluripotent stem cells by activating hypoxia related genes. Scientific Reports, 4:5228 (2014). ISSN 2045-2322. doi:10.1038/srep05228.
[29] Morikawa H, Ohkura N, Vandenbon A, Itoh M, Nagao-Sato S, Kawaji H, Lassmann T, Carninci P, Hayashizaki Y, Forrest ARR, Standley DM, Date H, Sakaguchi S, FANTOM Consortium. Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation. Proceedings of the National Academy of Sciences of the United States of America, 111(14):5289–5294 (2014). ISSN 1091-6490. doi:10.1073/pnas.1312717110.
[28] Pooley C, Ruau D, Lombard P, Göttgens B, Joshi A. TRES predicts transcription control in embryonic stem cells. Bioinformatics, 30(20):2983–2985 (2014). ISSN 1367-4811. doi: 10.1093/bioinformatics/btu399.
[27] Joshi A. Mammalian transcriptional hotspots are enriched for tissue specific enhancers near cell type specific highly expressed genes and are predicted to act as transcriptional activator hubs. BMC Bioinformatics, 15:412 (2014). ISSN 1471-2105. doi:10.1186/s12859-014-0412-0.
[26] Joshi A, Göttgens B. Concerted bioinformatic analysis of the genome-scale blood transcription factor compendium reveals new control mechanisms. Molecular BioSystems, 10(11):2935–2941 (2014). ISSN 1742-2051. doi:10.1039/c4mb00354c.
[25] Wishart TM, Mutsaers CA, Riessland M, Reimer MM, Hunter G, Hannam ML, Eaton SL, Fuller HR, Roche SL, Somers E, Morse R, Young PJ, Lamont DJ, Hammerschmidt M, Joshi A, Hohenstein P, Morris GE, Parson SH, Skehel PA, Becker T, Robinson IM, Becker CG, Wirth B, Gillingwater TH. Dysregulation of ubiquitin homeostasis and beta-catenin signaling promote spinal muscular atrophy. The Journal of Clinical Investigation, 124(4):1821–1834 (2014). ISSN 1558-8238. doi:10.1172/JCI71318.
[24] Gossner A, Wilkie H, Joshi A, Hopkins J. Exploring the abomasal lymph node transcriptome for genes associated with resistance to the sheep nematode Teladorsagia circumcincta. Veterinary Research, 44:68 (2013). ISSN 1297-9716. doi:10.1186/1297-9716-44-68.
[23] Moignard V, Macaulay IC, Swiers G, Buettner F, SchÃijtte J, Calero-Nieto FJ, Kinston S, Joshi A, Hannah R, Theis FJ, Jacobsen SE, de Bruijn MF, Göttgens B. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis. Nature Cell Biology, 15(4):363–372 (2013). ISSN 1476-4679. doi:10.1038/ncb2709.
[22] Swiers G, Baumann C, O’Rourke J, Giannoulatou E, Taylor S, Joshi A, Moignard V, Pina C, Bee T, Kokkaliaris KD, Yoshimoto M, Yoder MC, Frampton J, Schroeder T, Enver T, Göttgens B, de Bruijn 3 MFTR. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nature Communications, 4:2924 (2013). ISSN 2041-1723. doi:10.1038/ncomms3924.
[21] Calero-Nieto FJ, Joshi A, Bonadies N, Kinston S, chan WI, Gudgin E, Pridans C, Landry JR, Kikuchi J, Huntly BJ, Gottgens B. HOX-mediated LMO2 expression in embryonic mesoderm is recapitulated in acute leukaemias Oncogene 32(48):5471-80 (2013). doi: 10.1038/onc.2013.175
[20] Joshi A, Hannah R, Diamanti E, Göttgens B. Gene set control analysis predicts hematopoietic control mechanisms from genome-wide transcription factor binding data. Experimental Hematology, 41(4):354– 366.e14 (2013). ISSN 1873-2399. doi:10.1016/j.exphem.2012.11.008.
[19] Martello G, Sugimoto T, Diamanti E, Joshi A, Hannah R, Ohtsuka S, Göttgens B, Niwa H, Smith A. Esrrb is a pivotal target of the Gsk3/Tcf3 axis regulating embryonic stem cell self-renewal. Cell Stem Cell, 11(4):491–504 (2012). ISSN 1875-9777. doi:10.1016/j.stem.2012.06.008.
[18] Mutasa-Göttgens ES, Joshi A, Holmes HF, Hedden P, Göttgens B. A new RNASeq-based reference transcriptome for sugar beet and its application in transcriptome-scale analysis of vernalization and gibberellin responses. BMC Genomics, 13:99 (2012). ISSN 1471-2164. doi:10.1186/1471-2164-13-99.
[17] Tanaka Y, Joshi A, Wilson NK, Kinston S, Nishikawa S, Göttgens B. The transcriptional programme controlled by Runx1 during early embryonic blood development. Developmental Biology, 366(2):404– 419 (2012). ISSN 1095-564X. doi:10.1016/j.ydbio.2012.03.024.
[16] Joshi A, Beck Y, Michoel T. Post-transcriptional regulatory networks play a key role in noise reduction that is conserved from micro-organisms to mammals. The FEBS Journal, 279(18):3501–3512 (2012). ISSN 1742-4658. doi:10.1111/j.1742-4658.2012.08571.x.
[15] Chan WI, Hannah RL, Dawson MA, Pridans C, Foster D, Joshi A, Göttgens B, Van Deursen JM, Huntly BJP. The transcriptional coactivator Cbp regulates self-renewal and differentiation in adult hematopoietic stem cells. Molecular and Cellular Biology, 31(24):5046–5060 (2011). ISSN 1098-5549. doi: 10.1128/MCB.05830-11.
[14] Hannah R, Joshi A, Wilson NK, Kinston S, Göttgens B. A compendium of genome-wide hematopoietic transcription factor maps supports the identification of gene regulatory control mechanisms. Experimental Hematology, 39(5):531–541 (2011). ISSN 1873-2399. doi:10.1016/j.exphem.2011.02.009.
[13] Michoel T, Joshi A, Nachtergaele B, Van de Peer Y. Enrichment and aggregation of topological motifs are independent organizational principles of integrated interaction networks. Molecular BioSystems, 7(10):2769–2778 (2011). ISSN 1742-2051. doi:10.1039/c1mb05241a.
[12] Joshi A, Göttgens B. Maximum parsimony analysis of gene expression profiles permits the reconstruction of developmental cell lineage trees. Developmental Biology, 353(2):440–447 (2011). ISSN 1095-564X. doi:10.1016/j.ydbio.2011.02.013.
[11] Joshi A, Van de Peer Y, Michoel T. Structural and functional organization of RNA regulons in the posttranscriptional regulatory network of yeast. Nucleic Acids Research, 39(21):9108–9117 (2011). ISSN 1362-4962. doi:10.1093/nar/gkr661.
[10] Tijssen MR, Cvejic A, Joshi A, Hannah RL, Ferreira R, Forrai A, Bellissimo DC, Oram SH, Smethurst PA, Wilson NK, Wang X, Ottersbach K, Stemple DL, Green AR, Ouwehand WH, Göttgens B. Genome-wide analysis of simultaneous GATA1/2, RUNX1, FLI1, and SCL binding in megakaryocytes identifies hematopoietic regulators. Developmental Cell, 20(5):597–609 (2011). ISSN 1878-1551. doi: 10.1016/j.devcel.2011.04.008.
[9] Bonnet E, Tatari M, Joshi A, Michoel T, Marchal K, Berx G, Van de Peer Y. Module network inference from a cancer gene expression data set identifies microRNA regulated modules. PloS One, 5(4):e10162 (2010). ISSN 1932-6203. doi:10.1371/journal.pone.0010162.
[8] Joshi A, Van Parys T, Van de Peer Y, Michoel T. Characterizing regulatory path motifs in integrated networks using perturbational data. Genome Biology, 11(3):R32 (2010). ISSN 1474-760X. doi:10.1186/gb- 2010-11-3-r32.4
[7] Michoel T, De Smet R, Joshi A, Marchal K, Van de Peer Y. Reverse-engineering transcriptional modules from gene expression data. Annals of the New York Academy of Sciences, 1158:36–43 (2009). ISSN 1749-6632. doi:10.1111/j.1749-6632.2008.03943.x.
[6] Michoel T, De Smet R, Joshi A, Van de Peer Y, Marchal K. Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks. BMC Systems Biology, 3:49 (2009). ISSN 1752-0509. doi:10.1186/1752-0509-3-49.
[5] Joshi A, De Smet R, Marchal K, Van de Peer Y, Michoel T. Module networks revisited: computational assessment and prioritization of model predictions. Bioinformatics, 25(4):490–496 (2009). ISSN 1367-4811. doi:10.1093/bioinformatics/btn658.
[4] Vermeirssen V, Joshi A, Michoel T, Bonnet E, Casneuf T, Van de Peer Y. Transcription regulatory networks in Caenorhabditis elegans inferred through reverse-engineering of gene expression profiles constitute biological hypotheses for metazoan development. Molecular BioSystems, 5(12):1817–1830 (2009). ISSN 1742-2051. doi:10.1039/B908108a.
[3] Joshi A, Van de Peer Y, Michoel T. Analysis of a Gibbs sampler method for model-based clustering of gene expression data. Bioinformatics, 24(2):176–183 (2008). ISSN 1367-4811. doi:10.1093/bioinformatics/btm562.
[2] Michoel T, Maere S, Bonnet E, Joshi A, Saeys Y, Van den Bulcke T, Van Leemput K, van Remortel P, Kuiper M, Marchal K, Van de Peer Y. Validating module network learning algorithms using simulated data. BMC Bioinformatics, 8 Suppl 2:S5 (2007). ISSN 1471-2105. doi:10.1186/1471-2105-8-S2-S5.
[1] Thakur KG, Joshi A, Gopal B. Structural and biophysical studies on two promoter recognition domains of the extra-cytoplasmic function sigma factor sigma(C) from Mycobacterium tuberculosis. The Journal of Biological Chemistry, 282(7):4711–4718 (2007). ISSN 0021-9258. doi:10.1074/jbc.M606283200.