Relevant bibliographies by topics / Gene expression pattern

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Gene expression pattern'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Gene expression pattern"

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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Gene expression pattern"

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Yu, Yu-yang Yao. "Alternative splicing pattern of the slowpoke gene /." Full text (PDF) from UMI/Dissertation Abstracts International, 2000. http://wwwlib.umi.com/cr/utexas/fullcit?p3004408.

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Bekele, Adane Mihret. "Gene expression and cytokine pattern of pulmonary tuberculosis patients and their contacts in Ethiopia." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71942.

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Thesis (PhD)--Stellenbosch University, 2013.<br>ENGLISH ABSTRACT: The immune response against M. tuberculosis is multifactorial, involving a network of innate and adaptive immune responses. Characterization of the immune response, a clear understanding of the dynamics and interplay of different arms of the immune response and the identification of infection-stage specific biomarkers are critical to allow the development of better tools for combating tuberculosis. In an attempt to identify such biomarkers, we studied pulmonary tuberculosis patients and their contacts in Addis Ababa, Ethio
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Karam, Sana. "Mechanisms of pattern formation in the developing cerebellum : role for Eph receptor gene family /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/10557.

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Kurra, Goutham. "Pattern Recognition in Large Dimensional and Structured Datasets." University of Cincinnati / OhioLINK, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1014322308.

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Yagi, Shunya. "Sex and strategy use matters for pattern separation, adult neurogenesis and immediate early gene expression in the hippocampus." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/54089.

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Adult neurogenesis in the dentate gyrus (DG) plays a crucial role for pattern separation and there are sex differences in the regulation of neurogenesis. Although sex differences, favoring males, in spatial navigation have been reported, it is not known whether there are sex differences in pattern separation. The current study was designed to determine whether there are sex differences in the ability for separating similar or distinct patterns, learning strategy choice, adult neurogenesis and immediate early gene (IEG) expression in the DG in response to pattern separation training. Male and f
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Hopitzan, Alexander A. "Expression of the Ank3 gene in rat skeletal muscle : gene structure, splice pattern, phylogenetic analysis, molecular identification and subcellular targeting of encoded ankyrins-G." Paris 6, 2005. http://www.theses.fr/2005PA066311.

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Desh, Heather Colleen. "MASSETER MUSCLE MYOSIN 1C GENE EXPRESSION: RELATIONSHIPS TO GROWTH FACTORS AND INFLUENCE ON FIBER-TYPE AND SKELETAL GROWTH PATTERN." Master's thesis, Temple University Libraries, 2012. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/172046.

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Oral Biology<br>M.S.<br>The presence of dentofacial deformities in humans is prevalent, with distortions in jaw growth affecting about 20% of people worldwide. Least is known about the genetic etiology of malocclusions, so it is the purpose of this study to identify genetic factors which influence jaw growth and examine how their expression correlates with vertical and sagittal malocclusions. Myostatin (MSTN) is a negative growth regulator which functions to inhibit excessive growth of muscle. Mice in which this gene was absent exhibited increased muscle mass and altered skeletal form, indicat
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Perry, Michael W. "Comparative evolution and development of the butterfly eyespot and a survey of wing pattern gene expression across butterfly families." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0015869.

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Carkacioglu, Levent. "Automated Biological Data Acquisition And Integration Using Machine Learning Techniques." Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610396/index.pdf.

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Since the initial genome sequencing projects along with the recent advances on technology, molecular biology and large scale transcriptome analysis result in data accumulation at a large scale. These data have been provided in different platforms and come from different laboratories therefore, there is a need for compilation and comprehensive analysis. In this thesis, we addressed the automatization of biological data acquisition and integration from these non-uniform data using machine learning techniques. We focused on two different mining studies in the scope of this thesis. In the first st
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Ayuso, Anna Maria E. "Automation of Drosophila gene expression pattern image annotation : development of web-based image annotation tool and application of machine learning methods." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66403.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 91-92).<br>Large-scale in situ hybridization screens are providing an abundance of spatio-temporal patterns of gene expression data that is valuable for understanding the mechanisms of gene regulation. Drosophila gene expression pattern images have been generated by the Berkeley Drosophila Genome Project (BDGP) for over 7,000 genes in over 90,000 digital images. These images are currently hand cu
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Books on the topic "Gene expression pattern"

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Krasnoshtein, Flora. Analysis of the pattern of expression of the fanconi anemia group C (Fac) gene during murine development. National Library of Canada, 1995.

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ISBRA 2010 (2010 Storrs, Conn.). Bioinformatics research and applications: 6th international symposium, ISBRA 2010, Storrs, CT, USA, May 23-26, 2010 : proceedings. Springer, 2010.

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1958-, Kimura Ren, ed. Genetic inheritance patterns. Nova Science Publishers, 2008.

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Biganzoli, Elia. Computational Intelligence Methods for Bioinformatics and Biostatistics: 8th International Meeting, CIBB 2011, Gargnano del Garda, Italy, June 30 – July 2, 2011, Revised Selected Papers. Springer Berlin Heidelberg, 2012.

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Hodaie, Mojgan. The effect of patterns of electrical stimulation on the expression of the preprotachykinin gene in rat superior cervical ganglion neurons. National Library of Canada, 1994.

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Law, David To Sang. Temporal pattern of gene expression during sporulation in saccharomyces cerevisiae. 1993.

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Hess, Karla Ann. Pattern of expression of the 4F-rnp gene transcripts in Drosophila melanogaster. 1994.

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Neuronal Differentiation of Embryonic Carcinoma Cells: Differential gene expression pattern of key genes during differentiation regime. LAP Lambert Academic Publishing, 2011.

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Said, Harun M., Adrian Staab, and Carsten Hagemann. Brain-Cancer Associated Tumor Marker Genes Expression Pattern in Humans. Nova Science Publishers, Incorporated, 2011.

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Saner, Catherine. Characterization of Drosophila melanogaster cytochrome P450 6A2: Gene structure, expression pattern and metabolic capacity towards procarcinogens. 1995.

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Book chapters on the topic "Gene expression pattern"

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Adhikari, Prem Raj, Bimal Babu Upadhyaya, Chen Meng, and Jaakko Hollmén. "Gene Selection in Time-Series Gene Expression Data." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24855-9_13.

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Tuna, Salih, and Mahesan Niranjan. "Cross-Platform Analysis with Binarized Gene Expression Data." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04031-3_38.

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Nagarajan, Radhakrishnan, Meenakshi Upreti, and Mariofanna Milanova. "Identifying Non-random Patterns from Gene Expression Profiles." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88436-1_26.

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Andisi, Kivisi C., and Abdirahman I. Abdi. "Analysis of var Gene Transcription Pattern Using DBLα Tags." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2189-9_14.

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AbstractThe Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) antigens, which are encoded by a multigene family called var genes, are exported and inserted onto the surface of the infected erythrocytes. PfEMP1 plays a key role in the pathogenesis of severe malaria and are major targets of naturally acquired immunity. Studying the expression pattern of var genes in P. falciparum clinical isolates is crucial for understanding disease mechanism and immunity to malaria. However, var genes are highly variable, which makes it difficult to study their expression in clinical isolates obtai
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Maji, Pradipta, and Sushmita Paul. "Identification of Disease Genes Using Gene Expression and Protein–Protein Interaction Data." In Scalable Pattern Recognition Algorithms. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05630-2_6.

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Olomola, Afolabi, and Sumeet Dua. "Bi-clustering of Gene Expression Data Using Conditional Entropy." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04031-3_22.

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Fassetti, Fabio, Simona E. Rombo, and Cristina Serrao. "Discriminating Graph Pattern Mining from Gene Expression Data." In Discriminative Pattern Discovery on Biological Networks. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63477-7_4.

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Chetty, Girija, and Madhu Chetty. "Multiclass Microarray Gene Expression Analysis Based on Mutual Dependency Models." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04031-3_5.

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Zhang, Shuzhong, Kun Wang, Bilian Chen, and Xiuzhen Huang. "A New Framework for Co-clustering of Gene Expression Data." In Pattern Recognition in Bioinformatics. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24855-9_1.

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Truong, Duy Tin, Roberto Battiti, and Mauro Brunato. "A Repeated Local Search Algorithm for BiClustering of Gene Expression Data." In Similarity-Based Pattern Recognition. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39140-8_19.

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Conference papers on the topic "Gene expression pattern"

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Tu, Xinzhuo, and Yuanyuan Li. "Gene Expression Pattern Recognition Algorithm Based on Deep Learning." In 2024 6th International Conference on Artificial Intelligence and Computer Applications (ICAICA). IEEE, 2024. https://doi.org/10.1109/icaica63239.2024.10823051.

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Chung, Youngmin, Ji Hun Ha, Kyeong Chan Im, and Joo Sang Lee. "Accurate Spatial Gene Expression Prediction by Integrating Multi-Resolution Features." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01101.

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Suk, Youjeong, Jaemin Jeon, and Inuk Jung. "LOCOS: A cosine based local gene expression pattern finding algorithm on time-series data." In 2024 IEEE International Conference on Big Data (BigData). IEEE, 2024. https://doi.org/10.1109/bigdata62323.2024.10825504.

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Kong, Chuisi, zhenchong wang, Qin Yan, et al. "Initial identification and analysis of the gene responsible for 2-hydroxyisoflavanone dehydratasedase in tobacco (Nicotiana tabacum) and its expression pattern." In 2024 Fourth International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2024), edited by Pier Paolo Piccaluga, Ahmed El-Hashash, and Xiangqian Guo. SPIE, 2024. http://dx.doi.org/10.1117/12.3044096.

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Mitra, P., and D. D. Majumder. "Feature selection and gene clustering from gene expression data." In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1334213.

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Yousri, Noha A., Mohamed S. Kamel, and Mohamed A. Ismail. "Pattern Cores And Connectedness in Cancer Gene Expression." In 2007 IEEE 7th International Symposium on BioInformatics and BioEngineering. IEEE, 2007. http://dx.doi.org/10.1109/bibe.2007.4375551.

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Xie, Xin-Ping, and Xuan-Hao Ding. "Gene expression pattern extraction based on wavelet analysis." In 2009 International Conference on Information and Automation (ICIA). IEEE, 2009. http://dx.doi.org/10.1109/icinfa.2009.5205112.

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. Shcherbakova, S. A., P. E. Karitskaya, A. S. Chesnokova, I. O. Karpets, I. V. Evgenov, and D. V. Tseylikman. "DIFFERENTIALLY EXPRESSED GENES PREDICTING RESPONSE TO TAMOXIFEN THERAPY IN BREAST CANCER PATIENTS." In OpenBio-2023. ИПЦ НГУ, 2023. http://dx.doi.org/10.25205/978-5-4437-1526-1-40.

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The study is aimed at finding genes mediating the response to tamoxifen therapy. Meta-analysis of the articles and the construction of gene networks revealed 7 genes that make a significant contribution to survival rates. For the purpose of validation, the approach of analysis of differential gene expression was chosen. The validation results revealed a high occurrence of the desired genes. The pattern of deviation of their expression from the reference values was combined with that indicated by other authors.
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Mishra, Shruti, Debahuti Mishra, and Sandeep Kumar Satapathy. "Fuzzy pattern tree approach for mining frequent patterns from gene expression data." In 2011 3rd International Conference on Electronics Computer Technology (ICECT). IEEE, 2011. http://dx.doi.org/10.1109/icectech.2011.5941718.

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YANG, TAO, XINLIN ZHAO, BINBIN LIN, TAO ZENG, SHUIWANG JI, and JIEPING YE. "AUTOMATED GENE EXPRESSION PATTERN ANNOTATION IN THE MOUSE BRAIN." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814644730_0015.

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Reports on the topic "Gene expression pattern"

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Brufsky, Adam M. Determination of a Unique Pattern of Gene Expression in Node Positive Breast Cancer Using Serial Analysis of Gene Expression (SAGE). Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada417855.

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Brufsky, Adam M. Determination of a Unique Pattern of Gene Expression in Node Positive Breast Cancer Using Serial Analysis of Gene Expression (SAGE). Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada424196.

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O'Connell, Peter. Can Gene Expression Pattern Analysis Predict Recurrence in Node-Negative Breast Cancer. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada427708.

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Immaneni, Anand, and Peter O'Connell. Can Gene Expression Pattern Analysis Predict Recurrence in Node-Negative Breast Cancer. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada417924.

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Stoica, Gerald E. Gene Regulation and Expression Pattern of the Growth Factor Pleiotrophin in Breast Cancer. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada420767.

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Shani, Moshe, and C. P. Emerson. Genetic Manipulation of the Adipose Tissue via Transgenesis. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7604929.bard.

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The long term goal of this study was to reduce caloric and fat content of beef and other red meats by means of genetic modification of the animal such that fat would not be accumulated. This was attempted by introducing into the germ line myogenic regulatory genes that would convert fat tissue to skeletal muscle. We first determined the consequences of ectopic expression of the myogenic regulatory gene MyoD1. It was found that deregulation of MyoD1 did not result in ectopic skeletal muscle formation but rather led to embryonic lethalities, probably due to its role in the control of the cell cy
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Lifschitz, Eliezer, and Elliot Meyerowitz. The Relations between Cell Division and Cell Type Specification in Floral and Vegetative Meristems of Tomato and Arabidopsis. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613032.bard.

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Meristems were the central issue of our project. Genes that are required for cell division, cell elongation, cell proliferation and cell fate were studied in the tomato system. The analysis of the dUTPase and threonine deaminase genes, along with the dissection of their regulatory regions is completed, while that of the RNR2 and PPO genes is at an advanced stage. All these genes were isolated in our laboratory. In addition, 8 different MADS box genes were studied in transgenic plants and their genetic relevances discovered. We have also shown that a given MADS box gene can modify the polarity
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Barash, Itamar, J. Mina Bissell, Alexander Faerman, and Moshe Shani. Modification of Milk Composition via Transgenesis: The Role of the Extracellular Matrix in Regulating Transgene Expression. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570558.bard.

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Altering milk composition via transgenesis depends on three main factors. (1) The availability of an efficient regulatory sequences for targeting transgene(s) to the mammary gland; (2) a reliable in vitro model to test the expression of transgenes prior to their introduction to the animal genome; and (3) better understanding of the major factors which determine the rate of gene expression and protein synthesis. The current studies provide the necessary means and knowledge to alter milk protein composition via transgenesis. The following specific goals were achieved: a: Identifying regulatory r
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Ohad, Nir, and Robert Fischer. Control of Fertilization-Independent Development by the FIE1 Gene. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7575290.bard.

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A fundamental problem in biology is to understand how fertilization initiates reproductive development. During plant reproduction, one sperm cell fuses with the egg to form an embryo, whereas a second sperm cell fuses with the adjacent central cell nucleus to form the endosperm tissue that supports embryo and/or seedling development. To understand the mechanisms that initiate reproduction, we have isolated mutants of Arabidopsis that allow for replication of the central cell and subsequent endosperm development without fertilization. In this project we have cloned the MEA gene and showed that
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Heifetz, Yael, and Michael Bender. Success and failure in insect fertilization and reproduction - the role of the female accessory glands. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7695586.bard.

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The research problem. Understanding of insect reproduction has been critical to the design of insect pest control strategies including disruptions of mate-finding, courtship and sperm transfer by male insects. It is well known that males transfer proteins to females during mating that profoundly affect female reproductive physiology, but little is known about the molecular basis of female mating response and no attempts have yet been made to interfere with female post-mating responses that directly bear on the efficacy of fertilization. The female reproductive tract provides a crucial environm
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