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Статті в журналах з теми "Gene expression pattern"

Автор: Grafiati

Опубліковано: 3 червня 2025

Оновлено: 31 липня 2025

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1

Tiwari, Manjul. "An gene expression pattern." Journal of Natural Science, Biology and Medicine 3, no. 1 (2012): 12. http://dx.doi.org/10.4103/0976-9668.95935.

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2

Kumar, Sudhir, Karthik Jayaraman, Sethuraman Panchanathan, Rajalakshmi Gurunathan, Ana Marti-Subirana, and Stuart J. Newfeld. "BEST: A Novel Computational Approach for Comparing Gene Expression Patterns From Early Stages of Drosophila melanogaster Development." Genetics 162, no. 4 (2002): 2037–47. http://dx.doi.org/10.1093/genetics/162.4.2037.

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Abstract Embryonic gene expression patterns are an indispensable part of modern developmental biology. Currently, investigators must visually inspect numerous images containing embryonic expression patterns to identify spatially similar patterns for inferring potential genetic interactions. The lack of a computational approach to identify pattern similarities is an impediment to advancement in developmental biology research because of the rapidly increasing amount of available embryonic gene expression data. Therefore, we have developed computational approaches to automate the comparison of ge

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3

Zhao, Weiguo, Rongfang Li, Dandan Chen, et al. "Cloning and expression pattern analysis of MmPOD12 gene in mulberry under abiotic stresses." Journal of Experimental Biology and Agricultural Sciences 4, VIS (2017): 698–705. http://dx.doi.org/10.18006/2016.4(vis).698.705.

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4

Shi, T., Y. Xu, M. J. Yang, et al. "Genetic variation, association analysis, and expression pattern of SMAD3 gene in Chinese cattle." Czech Journal of Animal Science 61, No. 5 (2016): 209–16. http://dx.doi.org/10.17221/34/2015-cjas.

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5

Wang, Y. P., L. Liang, B. C. Han, et al. "GEPS: the Gene Expression Pattern Scanner." Nucleic Acids Research 34, Web Server (2006): W492—W497. http://dx.doi.org/10.1093/nar/gkl067.

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6

Henry, Stephen P., Masamine Takanosu, Tanya C. Boyd, et al. "Expression Pattern and Gene Characterization ofAsporin." Journal of Biological Chemistry 276, no. 15 (2001): 12212–21. http://dx.doi.org/10.1074/jbc.m011290200.

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We have discovered a new member of the class I small leucine-rich repeat proteoglycan (SLRP) family which is distinct from the other class I SLRPs since it possesses a unique stretch of aspartate residues at its N terminus. For this reason, we called the moleculeasporin. The deduced amino acid sequence is about 50% identical (and 70% similar) to decorin and biglycan. However, asporin does not contain a serine/glycine dipeptide sequence required for the assembly ofO-linked glycosaminoglycans and is probably not a proteoglycan. The tissue expression ofasporinpartially overlaps with the expressio

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7

Mulieri, Philip J., Ami Okada, David A. Sassoon, Susan K. Mcconnell, and Robert S. Krauss. "Developmental expression pattern of thecdo gene." Developmental Dynamics 219, no. 1 (2000): 40–49. http://dx.doi.org/10.1002/1097-0177(2000)9999:9999<::aid-dvdy1032>3.0.co;2-m.

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8

Orlowski, Michael. "Gene expression inMucordimorphism." Canadian Journal of Botany 73, S1 (1995): 326–34. http://dx.doi.org/10.1139/b95-263.

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An ongoing dialectic has concerned the relative importance of differential gene expression versus the pattern of new wall deposition in Mucor dimorphism. Numerous physiological processes and enzyme activities have been observed in flux during morphogenesis, but a causal link to dimorphism has been infrequently demonstrated. Very few of the proteins that are conspicuous in two-dimensional polyacrylamide gel electrophoresis are specific to cell morphology or significantly change in amount during morphogenesis. Cyclic AMP, putrescine, S-adenosylmethionine, and enzymes governing their intracellula

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9

Majka, Maciej, Nils B. Becker, Pieter Rein ten Wolde, Marcin Zagorski, and Thomas R. Sokolowski. "Stable developmental patterns of gene expression without morphogen gradients." PLOS Computational Biology 20, no. 12 (2024): e1012555. https://doi.org/10.1371/journal.pcbi.1012555.

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Gene expression patterns in developing organisms are established by groups of cross-regulating target genes that are driven by morphogen gradients. As development progresses, morphogen activity is reduced, leaving the emergent pattern without stabilizing positional cues and at risk of rapid deterioration due to the inherently noisy biochemical processes at the cellular level. But remarkably, gene expression patterns remain spatially stable and reproducible over long developmental time spans in many biological systems. Here we combine spatial-stochastic simulations with an enhanced sampling met

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10

Wang, Minzhi, Gao Chen, Cheng Lu, et al. "Rheumatoid Arthritis with Deficiency Pattern in Traditional Chinese Medicine Shows Correlation with Cold and Hot Patterns in Gene Expression Profiles." Evidence-Based Complementary and Alternative Medicine 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/248650.

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In our precious study, the correlation between cold and hot patterns in traditional Chinese medicine (TCM) and gene expression profiles in rheumatoid arthritis (RA) has been explored. Based on TCM theory, deficiency pattern is another key pattern diagnosis among RA patients, which leads to a specific treatment principle in clinical management. Therefore, a further analysis was performed aiming at exploring the characteristic gene expression profile of deficiency pattern and its correlation with cold and hot patterns in RA patients by bioinformatics analysis approach based on gene expression pr

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11

Sun, Y. H., C. J. Tsai, M. M. Green, et al. "White as a reporter gene to detect transcriptional silencers specifying position-specific gene expression during Drosophila melanogaster eye development." Genetics 141, no. 3 (1995): 1075–86. http://dx.doi.org/10.1093/genetics/141.3.1075.

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Abstract The white+ gene was used as a reporter to detect transcriptional silencer activity in the Drosophila genome. Changes in the spatial expression pattern of white were scored in the adult eye as nonuniform patterns of pigmentation. Thirty-six independent P[lacW] transposant lines were collected. These represent 12 distinct pigmentation patterns and probably 21 loci. The spatial pigmentation pattern is due to cis-acting suppression of white+ expression, and the suppression probably depends on cell position rather than cell type. The mechanism of suppression differs from inactivation by he

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12

Mora-Martinez, Carlos. "Expression pattern determines regulatory logic." PLOS ONE 16, no. 1 (2021): e0244864. http://dx.doi.org/10.1371/journal.pone.0244864.

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Large amounts of effort have been invested in trying to understand how a single genome is able to specify the identity of hundreds of cell types. Inspired by some aspects of Caenorhabditis elegans biology, we implemented an in silico evolutionary strategy to produce gene regulatory networks (GRNs) that drive cell-specific gene expression patterns, mimicking the process of terminal cell differentiation. Dynamics of the gene regulatory networks are governed by a thermodynamic model of gene expression, which uses DNA sequences and transcription factor degenerate position weight matrixes as input.

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13

Lu, Cheng, Xuyan Niu, Cheng Xiao, et al. "Network-Based Gene Expression Biomarkers for Cold and Heat Patterns of Rheumatoid Arthritis in Traditional Chinese Medicine." Evidence-Based Complementary and Alternative Medicine 2012 (2012): 1–17. http://dx.doi.org/10.1155/2012/203043.

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In Traditional Chinese Medicine (TCM), patients with Rheumatoid Arthritis (RA) can be classified into two main patterns: cold-pattern and heat-pattern. This paper identified the network-based gene expression biomarkers for both cold- and heat-patterns of RA. Gene expression profilings of CD4+ T cells from cold-pattern RA patients, heat-pattern RA patients, and healthy volunteers were obtained using microarray. The differentially expressed genes and related networks were explored using DAVID, GeneSpring software, and the protein-protein interactions (PPI) method. EIF4A2, CCNT1, and IL7R, which

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14

LaPointe, Lawrence C., Robert Dunne, Glenn S. Brown, et al. "Map of differential transcript expression in the normal human large intestine." Physiological Genomics 33, no. 1 (2008): 50–64. http://dx.doi.org/10.1152/physiolgenomics.00185.2006.

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While there is considerable research related to using differential gene expression to predict disease phenotype classification, e.g., neoplastic tissue from nonneoplastic controls, there is little understanding of the range of expression in normal tissues. Understanding patterns of gene expression in nonneoplastic tissue, including regional anatomic expression changes within an organ, is vital to understanding gene expression changes in diseased tissue. To explore the gene expression change along the proximal-distal axis of the large intestine, we analyzed microarray data in 184 normal human s

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15

Shan, Qiu Fu, Ji Hua Feng, Ying Lu, Zen Hui Shan, and Pan Feng Chen. "Nucleosome Positioning in the Upstream of TSS from Different Expression Pattern Gene during Drosophila embryogenesis." Advanced Materials Research 934 (May 2014): 182–87. http://dx.doi.org/10.4028/www.scientific.net/amr.934.182.

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Some significant differences about nucleosome positioning of different expression patterns gene have been found while researching the nucleosome positioning of Drosophila embryogenesis. The difference from the previous study was the restricted expression pattern gene incorporating H2A.Z into the-1 nucleosome in the upstream of Transcription Start Sites (TSS). Interestingly, compared with the nucleosome positioning of yeast genes, this nucleosome arrangement at gene of restricted expression pattern is similar with the characteristic found in yeast.

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16

Henrich, T. "MEPD: a Medaka gene expression pattern database." Nucleic Acids Research 31, no. 1 (2003): 72–74. http://dx.doi.org/10.1093/nar/gkg017.

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17

Wang, Daifeng, Ari Arapostathis, Claus O. Wilke, and Mia K. Markey. "Principal-Oscillation-Pattern Analysis of Gene Expression." PLoS ONE 7, no. 1 (2012): e28805. http://dx.doi.org/10.1371/journal.pone.0028805.

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18

Nam, D., and S. Y. Kim. "Gene-set approach for expression pattern analysis." Briefings in Bioinformatics 9, no. 3 (2008): 189–97. http://dx.doi.org/10.1093/bib/bbn001.

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19

Nam, D., and S. Y. Kim. "Gene-set approach for expression pattern analysis." Briefings in Bioinformatics 9, no. 5 (2008): 450. http://dx.doi.org/10.1093/bib/bbn030.

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20

Frank, Derk, Christian Kuhn, Benedikt Brors, et al. "Gene Expression Pattern in Biomechanically Stretched Cardiomyocytes." Hypertension 51, no. 2 (2008): 309–18. http://dx.doi.org/10.1161/hypertensionaha.107.098046.

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21

Falcke, Martin, and Herbert Levine. "Pattern Selection by Gene Expression inDictyostelium Discoideum." Physical Review Letters 80, no. 17 (1998): 3875–78. http://dx.doi.org/10.1103/physrevlett.80.3875.

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22

Smallwood, M. F., S. J. Gurr, M. J. McPherson, K. Roberts, and D. J. Bowles. "The pattern of plant annexin gene expression." Biochemical Journal 281, no. 2 (1992): 501–5. http://dx.doi.org/10.1042/bj2810501.

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Peptide sequence data derived from a plant annexin, P34 [Smallwood, Keen & Bowles (1990) Biochem. J. 270, 157-161] was used to design amplimers for PCR. A unique fragment of 95 bp, amplified from tomato (Lycopersicon esculertum) genomic DNA, was used in Northern analyses and demonstrated a differential pattern of expression in vegetative tissues of tomato, potato (Solanum tuberosum) and barley (Hordeum vulgare). The tissue-specific abundance of the annexin transcript was found to correlate closely with abundance of annexin protein as revealed by their partial purification and analysis with

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23

Jiang, J., Z. Xu, X. Han, F. Wang, and L. Wang. "The pattern of development for gene expression of sterol regulatory element binding transcription factor 1 in pigs." Czech Journal of Animal Science 51, No. 6 (2011): 248–52. http://dx.doi.org/10.17221/3936-cjas.

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Sterol regulatory element-binding transcription factor 1 (SREBF1) has been implicated as a key regulator of adipocyte differentiation and lipid metabolism. The pattern of SREBF1 gene expression in different growth stages and the relation with adipose deposition is studied. Fifteen female Duroc &times; Landrace &times; Yorkshire pigs in five groups, each group of three pigs at live weight 1, 30, 50, 70 and 90 kg, were used to study the developmental gene expression of SREBF1 in the subcutaneous adipose tissue by means of semi-quantitative RT-PCR. The results showed that porcine SREBF1 m

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24

Tsai, C., and J. P. Gergen. "Gap gene properties of the pair-rule gene runt during Drosophila segmentation." Development 120, no. 6 (1994): 1671–83. http://dx.doi.org/10.1242/dev.120.6.1671.

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The Drosophila Runt protein is a member of a new family of transcriptional regulators that have important roles in processes extending from pattern formation in insect embryos to leukemogenesis in humans. We used ectopic expression to investigate runt's function in the pathway of Drosophila segmentation. Transient over-expression of runt under the control of a Drosophila heat-shock promoter caused stripe-specific defects in the expression patterns of the pair-rule genes hairy and even-skipped but had a more uniform effect on the secondary pair-rule gene fushi tarazu. Surprisingly, the expressi

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25

Kraut, R., and M. Levine. "Spatial regulation of the gap gene giant during Drosophila development." Development 111, no. 2 (1991): 601–9. http://dx.doi.org/10.1242/dev.111.2.601.

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We describe the regulated expression of the segmentation gene giant (gt) during early embryogenesis. The gt protein is expressed in two broad gradients in precellular embryos, one in anterior regions and the other in posterior regions. Double immunolocalization studies show that the gt patterns overlap with protein gradients specified by the gap genes hunchback (hb) and knirps (kni). Analysis of all known gap mutants, as well as mutations that disrupt each of the maternal organizing centers, indicate that maternal factors are responsible for initiating gt expression, while gap genes participat

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26

Takao, Keizo, та Tsuyoshi Miyakawa. "Hippocampal gene gene expression pattern analysis in α-CaMKII+/− mice". Neuroscience Research 65 (січень 2009): S127. http://dx.doi.org/10.1016/j.neures.2009.09.614.

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27

Takada, Norio, Taichiro Goto, and Nori Satoh. "Expression pattern of theBrachyury gene in the arrow wormparaspadella gotoi (chaetognatha)." genesis 32, no. 3 (2002): 240–45. http://dx.doi.org/10.1002/gene.10077.

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28

Waldén, Tomas B., Ida R. Hansen, James A. Timmons, Barbara Cannon, and Jan Nedergaard. "Recruited vs. nonrecruited molecular signatures of brown, “brite,” and white adipose tissues." American Journal of Physiology-Endocrinology and Metabolism 302, no. 1 (2012): E19—E31. http://dx.doi.org/10.1152/ajpendo.00249.2011.

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Mainly from cell culture studies, a series of genes that have been suggested to be characteristic of different types of adipocytes have been identified. Here we have examined gene expression patterns in nine defined adipose depots: interscapular BAT, cervical BAT, axillary BAT, mediastinic BAT, cardiac WAT, inguinal WAT, retroperitoneal WAT, mesenteric WAT, and epididymal WAT. We found that each depot displayed a distinct gene expression fingerprint but that three major types of depots were identifiable: the brown, the brite, and the white. Although differences in gene expression pattern were

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29

Sääf, Annika M., Jennifer M. Halbleib, Xin Chen, et al. "Parallels between Global Transcriptional Programs of Polarizing Caco-2 Intestinal Epithelial Cells In Vitro and Gene Expression Programs in Normal Colon and Colon Cancer." Molecular Biology of the Cell 18, no. 11 (2007): 4245–60. http://dx.doi.org/10.1091/mbc.e07-04-0309.

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Posttranslational mechanisms are implicated in the development of epithelial cell polarity, but little is known about the patterns of gene expression and transcriptional regulation during this process. We characterized temporal patterns of gene expression during cell–cell adhesion-initiated polarization of cultured human Caco-2 cells, which develop structural and functional polarity resembling enterocytes in vivo. A distinctive switch in gene expression patterns occurred upon formation of cell–cell contacts. Comparison to gene expression patterns in normal human colon and colon tumors revealed

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30

Stamova, Boryana S., Debbie Laudencia-Chingcuanco, and Diane M. Beckles. "Transcriptomic Analysis of Starch Biosynthesis in the Developing Grain of Hexaploid Wheat." International Journal of Plant Genomics 2009 (March 8, 2009): 1–23. http://dx.doi.org/10.1155/2009/407426.

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The expression of genes involved in starch synthesis in wheat was analyzed together with the accumulation profiles of soluble sugars, starch, protein, and starch granule distribution in developing caryopses obtained from the same biological materials used for profiling of gene expression using DNA microarrays. Multiple expression patterns were detected for the different starch biosynthetic gene isoforms, suggesting their relative importance through caryopsis development. Members of the ADP-glucose pyrophosphorylase, starch synthase, starch branching enzyme, and sucrose synthase gene families s

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31

Schaner, Marci E., Douglas T. Ross, Giuseppe Ciaravino, et al. "Gene Expression Patterns in Ovarian Carcinomas." Molecular Biology of the Cell 14, no. 11 (2003): 4376–86. http://dx.doi.org/10.1091/mbc.e03-05-0279.

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We used DNA microarrays to characterize the global gene expression patterns in surface epithelial cancers of the ovary. We identified groups of genes that distinguished the clear cell subtype from other ovarian carcinomas, grade I and II from grade III serous papillary carcinomas, and ovarian from breast carcinomas. Six clear cell carcinomas were distinguished from 36 other ovarian carcinomas (predominantly serous papillary) based on their gene expression patterns. The differences may yield insights into the worse prognosis and therapeutic resistance associated with clear cell carcinomas. A co

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32

Wang, Chunyan, Yiqing Xu, Xuelin Wang, et al. "GEsture: an online hand-drawing tool for gene expression pattern search." PeerJ 6 (June 20, 2018): e4927. http://dx.doi.org/10.7717/peerj.4927.

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Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a ‘desirable’ or ‘user-defined’ pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clu

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33

Hansen, C., A. Fu, C. Li, W. T. Dixon, R. Christopherson, and S. S. Moore. "Global gene expression patterns spanning 3T3-L1 preadipocyte differentiation." Canadian Journal of Animal Science 84, no. 3 (2004): 367–76. http://dx.doi.org/10.4141/a03-120.

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Adipogenesis is of significant relevance from an agricultural perspective. Traits such as subcutaneous fat thickness, marbling and waste fat are of substantial economic importance in animal production. In order to discover more about the genetic basis of this process, a study was undertaken to examine the changes that occur daily in global gene expression as 3T3-L1 cells differentiate from preadipocyte to adipocyte. Duplicate RNA samples were collected daily during the differentiation process and probed with the Affymetrix U74Av2 GeneChip® microarray to allow the time-course analysis of the ge

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34

Muszyński, Michał, and Stanisław Osowski. "Data mining methods for gene selection on the basis of gene expression arrays." International Journal of Applied Mathematics and Computer Science 24, no. 3 (2014): 657–68. http://dx.doi.org/10.2478/amcs-2014-0048.

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Abstract The paper presents data mining methods applied to gene selection for recognition of a particular type of prostate cancer on the basis of gene expression arrays. Several chosen methods of gene selection, including the Fisher method, correlation of gene with a class, application of the support vector machine and statistical hypotheses, are compared on the basis of clustering measures. The results of applying these individual selection methods are combined together to identify the most often selected genes forming the required pattern, best associated with the cancerous cases. This resul

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35

Caprioli, Arianna, Hongxin Zhu, and Thomas N. Sato. "CRBP-III:lacZ expression pattern reveals a novel heterogeneity of vascular endothelial cells." genesis 40, no. 3 (2004): 139–45. http://dx.doi.org/10.1002/gene.20075.

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36

Johnson, Grace E., Chenyi Fei, Ned S. Wingreen, and Bonnie L. Bassler. "Analysis of gene expression within individual cells reveals spatiotemporal patterns underlying Vibrio cholerae biofilm development." PLOS Biology 23, no. 5 (2025): e3003187. https://doi.org/10.1371/journal.pbio.3003187.

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Bacteria commonly exist in multicellular, surface-attached communities called biofilms. Biofilms are central to ecology, medicine, and industry. The Vibrio cholerae pathogen forms biofilms from single founder cells that, via cell division, mature into three-dimensional structures with distinct, yet reproducible, regional architectures. To define mechanisms underlying biofilm developmental transitions, we establish a single-molecule fluorescence in situ hybridization (smFISH) approach that enables accurate quantitation of spatiotemporal gene-expression patterns in biofilms at cell-scale resolut

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37

Pooja, Pandey* Jai Pratap Dixit Brijesh Kumar Pandey. "CLUSTERING ALGORITHMS- FOR GENE EXPRESSION ANALYSIS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 12 (2016): 204–18. https://doi.org/10.5281/zenodo.192575.

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Data Mining refers to as the nontrivial process of “identifying valid, novel, potentially useful and ultimately understandable pattern in data". Based on the type of knowledge that is mined, data mining can be classified in to different models such as Clustering, Decision trees, Association rules, and Sequential pattern and time series. In this paper work, an attempt has been made to study theoretical background and applications of Clustering techniques in data mining with a special emphasis on analysis of Gene Expression under Bioinformatics. Bioinformatics is the study of genetic and other b

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38

Raja, Komal K. B., Mujeeb O. Shittu, Peter M. E. Nouhan, et al. "The regulation of a pigmentation gene in the formation of complex color patterns in Drosophila abdomens." PLOS ONE 17, no. 12 (2022): e0279061. http://dx.doi.org/10.1371/journal.pone.0279061.

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Changes in the control of developmental gene expression patterns have been implicated in the evolution of animal morphology. However, the genetic mechanisms underlying complex morphological traits remain largely unknown. Here we investigated the molecular mechanisms that induce the pigmentation gene yellow in a complex color pattern on the abdomen of Drosophila guttifera. We show that at least five developmental genes may collectively activate one cis-regulatory module of yellow in distinct spot rows and a dark shade to assemble the complete abdominal pigment pattern of Drosophila guttifera. O

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39

QIU, Zhishan, Ying SHENG, and Feng JIAO. "The Discriminative Conditions for the Distribution Pattern of Expression Products in Stochastic Gene Expression Models." Journal of Chinese Statistical Sciences 3, no. 1 (2025): 15–25. https://doi.org/10.48014/jcss.20250201001.

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Gene expression is essentially a random process. The distribution of expression product quantities can comprehensively describe the stochastic behavior. of gene expression, which typically exhibits three distribution shapes: decaying, bell-shaped, and bimodal. Ref. [21] explores a stochastic gene expression model of minimal coupled positive-plus-negative feedback loop. By constructing two continuous curves C1 and C2 in the parameter phase, the necessary and sufficient conditions for the model to generate three distribution shapes were theoretically provided. However, for any given set of param

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40

Hashimoto, Tomoki, Michael T. Lawton, Gen Wen, et al. "Gene Microarray Analysis of Human Brain Arteriovenous Malformations." Neurosurgery 54, no. 2 (2004): 410–25. http://dx.doi.org/10.1227/01.neu.0000103421.35266.71.

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Abstract OBJECTIVE Human brain arteriovenous malformations (BAVMs) display abnormal expression of various angiogenesis-related genes and their products. We examined gene expression patterns in BAVMs by the gene microarray technique. METHODS We analyzed BAVM and control brain samples obtained by temporal lobectomy for medically intractable seizure by Affymetrix Human Gene Set U95Av2 (Affymetrix, Inc., Santa Clara, CA). The gene microarray data were compared with new and previously published data that used conventional molecular biology techniques. RESULTS We analyzed six BAVM and five control b

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Vimala, K., and D. Usha. "COMPUTATIONAL ANALYSIS ON GENE EXPRESSION PATTERN: A SURVEY." International Journal of Advanced Research 6, no. 6 (2018): 739–44. http://dx.doi.org/10.21474/ijar01/7270.

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Fassetti, Fabio, Simona E. Rombo, and Cristina Serrao. "Discriminating graph pattern mining from gene expression data." ACM SIGAPP Applied Computing Review 16, no. 3 (2016): 26–36. http://dx.doi.org/10.1145/3015297.3015300.

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Mathioudaki, K., A. Papadokostopoulou, A. Scorilas, D. Xynopoulos, N. Agnanti, and M. Talieri. "The PRMT1 gene expression pattern in colon cancer." British Journal of Cancer 99, no. 12 (2008): 2094–99. http://dx.doi.org/10.1038/sj.bjc.6604807.

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Hirning-Folz, Ulrike, Monika Wilda, Volkhard Rippe, Jörn Bullerdiek, and Horst Hameister. "The expression pattern of theHmgic gene during development." Genes, Chromosomes and Cancer 23, no. 4 (1998): 350–57. http://dx.doi.org/10.1002/(sici)1098-2264(199812)23:4<350::aid-gcc10>3.0.co;2-e.

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Markowitz, A. J., G. D. Wu, E. H. Birkenmeier, and P. G. Traber. "The human sucrase-isomaltase gene directs complex patterns of gene expression in transgenic mice." American Journal of Physiology-Gastrointestinal and Liver Physiology 265, no. 3 (1993): G526—G539. http://dx.doi.org/10.1152/ajpgi.1993.265.3.g526.

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Sucrase-isomaltase (SI) is an enterocyte-specific gene that is expressed in complex developmental and spatial patterns. In this study, we examine the ability of regulatory elements within the human SI (hSI) gene to direct appropriate cell lineage and spatial patterns of expression in transgenic mice. Transgenic mouse lines were established using a construct containing bases -3424 to +54 of the hSI gene linked to the human growth hormone (hGH) structural gene. In each transgenic line, hGH mRNA and protein were expressed only in the small intestine and colon. In contrast to the endogenous mouse

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Okamoto, Shotaro, Kohei Negishi, Yuko Toyama, Takeo Ushijima, and Kengo Morohashi. "Leaf Trichome Distribution Pattern in Arabidopsis Reveals Gene Expression Variation Associated with Environmental Adaptation." Plants 9, no. 7 (2020): 909. http://dx.doi.org/10.3390/plants9070909.

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Gene expression varies stochastically even in both heterogenous and homogeneous cell populations. This variation is not simply useless noise; rather, it is important for many biological processes. Unicellular organisms or cultured cell lines are useful for analyzing the variation in gene expression between cells; however, owing to technical challenges, the biological relevance of this variation in multicellular organisms such as higher plants remain unclear. Here, we addressed the biological relevance of this variation between cells by examining the genetic basis of trichome distribution patte

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Chen, Huaping, Tao Xia, Lei Zhou, et al. "Gene organization, alternate splicing and expression pattern of porcine visfatin gene." Domestic Animal Endocrinology 32, no. 3 (2007): 235–45. http://dx.doi.org/10.1016/j.domaniend.2006.03.004.

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Inoue, Masayo, and Katsuhisa Horimoto. "Relationship between regulatory pattern of gene expression level and gene function." PLOS ONE 12, no. 5 (2017): e0177430. http://dx.doi.org/10.1371/journal.pone.0177430.

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Roberts, N. A., J. A. Sloane-Stanley, J. A. Sharpe, S. J. Stanworth, and W. G. Wood. "Globin Gene Switching in Transgenic Mice Carrying HS2-Globin Gene Constructs." Blood 89, no. 2 (1997): 713–23. http://dx.doi.org/10.1182/blood.v89.2.713.

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Abstract We have examined the pattern of human globin gene switching in transgenic mice containing three different γ and β gene constructs (HS2GγAγδβ, HS2Aγβneo, and HS2Aγenβ) and compared the results with previously described transgenics (HS2Aγβ, HS2GγAγ-117δβ, and LCRεGγAγδβ). Developmental regulation was observed in all cases with identical patterns in lines bearing the same construct. Three different patterns of switching were observed: LCRεGγAγδβ and HS2Aγβneo mice switched rapidly, HS2GγAγδβ and HS2GγAγ-117δβ at an intermediate rate, and HS2Aγβ and HS2Aγenβ mice showed delayed switching,

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JIAO, YUHUA, BRUCE A. ROSA, SOOKYUNG OH, BERONDA L. MONTGOMERY, WENSHENG QIN, and JIN CHEN. "DETECTION AND DECOMPOSITION: TREATMENT-INDUCED CYCLIC GENE EXPRESSION DISRUPTION IN HIGH-THROUGHPUT TIME-SERIES DATASETS." Journal of Bioinformatics and Computational Biology 10, no. 06 (2012): 1271002. http://dx.doi.org/10.1142/s0219720012710023.

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Higher organisms possess many genes which cycle under normal conditions, to allow the organism to adapt to expected environmental conditions throughout the course of a day. However, treatment-induced disruption of regular cyclic gene expression patterns presents a significant challenge in novel gene discovery experiments because these disruptions can induce strong differential regulation events for genes that are not involved in an adaptive response to the treatment. To address this cycle disruption problem, we reviewed the state-of-art periodic pattern detection algorithms and a pattern decom

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