Academic literature on the topic '3D genome structure'
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Journal articles on the topic "3D genome structure"
Zhou, Tianming, Ruochi Zhang, and Jian Ma. "The 3D Genome Structure of Single Cells." Annual Review of Biomedical Data Science 4, no. 1 (July 20, 2021): 21–41. http://dx.doi.org/10.1146/annurev-biodatasci-020121-084709.
Full textMohanta, Tapan Kumar, Awdhesh Kumar Mishra, and Ahmed Al-Harrasi. "The 3D Genome: From Structure to Function." International Journal of Molecular Sciences 22, no. 21 (October 27, 2021): 11585. http://dx.doi.org/10.3390/ijms222111585.
Full textHuang, Kai, Yue Li, Anne R. Shim, Ranya K. A. Virk, Vasundhara Agrawal, Adam Eshein, Rikkert J. Nap, Luay M. Almassalha, Vadim Backman, and Igal Szleifer. "Physical and data structure of 3D genome." Science Advances 6, no. 2 (January 2020): eaay4055. http://dx.doi.org/10.1126/sciadv.aay4055.
Full textHeinz, Sven, Lorane Texari, Michael G. B. Hayes, Matthew Urbanowski, Max W. Chang, Ninvita Givarkes, Alexander Rialdi, et al. "Transcription Elongation Can Affect Genome 3D Structure." Cell 174, no. 6 (September 2018): 1522–36. http://dx.doi.org/10.1016/j.cell.2018.07.047.
Full textWlasnowolski, Michal, Michal Sadowski, Tymon Czarnota, Karolina Jodkowska, Przemyslaw Szalaj, Zhonghui Tang, Yijun Ruan, and Dariusz Plewczynski. "3D-GNOME 2.0: a three-dimensional genome modeling engine for predicting structural variation-driven alterations of chromatin spatial structure in the human genome." Nucleic Acids Research 48, W1 (May 22, 2020): W170—W176. http://dx.doi.org/10.1093/nar/gkaa388.
Full textShepherd, Jeremiah J., Lingxi Zhou, William Arndt, Yan Zhang, W. Jim Zheng, and Jijun Tang. "Exploring genomes with a game engine." Faraday Discuss. 169 (2014): 443–53. http://dx.doi.org/10.1039/c3fd00152k.
Full textPoblete, Simón, and Horacio V. Guzman. "Structural 3D Domain Reconstruction of the RNA Genome from Viruses with Secondary Structure Models." Viruses 13, no. 8 (August 6, 2021): 1555. http://dx.doi.org/10.3390/v13081555.
Full textTrieu, Tuan, and Jianlin Cheng. "3D genome structure modeling by Lorentzian objective function." Nucleic Acids Research 45, no. 3 (November 28, 2016): 1049–58. http://dx.doi.org/10.1093/nar/gkw1155.
Full textLi, Chao, Xiao Dong, Haiwei Fan, Chuan Wang, Guohui Ding, and Yixue Li. "The 3DGD: a database of genome 3D structure." Bioinformatics 30, no. 11 (February 12, 2014): 1640–42. http://dx.doi.org/10.1093/bioinformatics/btu081.
Full textTjong, Harianto, Wenyuan Li, Reza Kalhor, Chao Dai, Shengli Hao, Ke Gong, Yonggang Zhou, et al. "Population-based 3D genome structure analysis reveals driving forces in spatial genome organization." Proceedings of the National Academy of Sciences 113, no. 12 (March 7, 2016): E1663—E1672. http://dx.doi.org/10.1073/pnas.1512577113.
Full textDissertations / Theses on the topic "3D genome structure"
Mendieta, Esteban Julen 1992. "Chromatin 3D modelling from sparse 3C-based datasets." Doctoral thesis, Universitat Pompeu Fabra, 2020. http://hdl.handle.net/10803/670311.
Full textLa organización espacial del genoma y la actividad transcripcional están estrechamente coordinadas para garantizar el correcto funcionamiento de la célula. Por lo tanto, se necesita una comprensión adecuada de la organización de la cromatina para profundizar en los procesos que regulan la actividad de loci de interés. Tecnologías basadas en la captura de conformación de cromatina (3C) han facilitado la comprensión de la arquitectura genómica. Particularmente, las tecnologías 3C sparse, como promoter capture Hi-C (pcHi-C), se han centrado en interacciones especificas de interés para desvelar el panorama de interacción asociado con elementos funcionales como los promotores. Sin embargo, para comprender adecuadamente los perfiles sparse de interacción de pcHi-C, es importante contextualizar la perspectiva 3D que subyace a estas interacciones. En esta tesis, hemos desarrollado una herramienta para el modelado y análisis 3D de datos sparse derivados de 3C como pcHi-C, y hemos probado su utilidad en la comprensión de la arquitectura reguladora de genes asociados con una actividad especifica del tipo celular o tejido.
Han, Chenggong. "Statistical models and computational methods for studying DNA differential methylation and 3D genome structure." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595417277891892.
Full textSegueni, Julie. "DNA methylation changes CTCF binding and reorganizes 3D genome structure in breast cancer cells." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASL020.
Full textMammalian genomes adopt a functional 3D organization where enhancer-promoter interactions are constrained within Topologically Associating Domains (TADs). The CTCF insulator protein has a dual role in this process, with binding at promoters resulting in the formation of enhancer-promoter loops (intra-TAD structure) and binding at TAD boundaries preventing the formation of inappropriate loops between neighboring domains. Importantly, perturbations of CTCF binding at specific sites in cancer cells can be caused by both changes to the DNA sequence (mutations) or DNA methylation changes (epi-mutations). We first performed precisely-calibrated CTCF ChIP-seq experiments and found that a large number of sites are differentially bound, with a substantial fraction of differential CTCF binding peaks shared among cancer cell lines. Differential CTCF peaks can both be gained and lost and are often localized close to genes associated with breast cancer transformation. We found a striking correlation between CTCF binding changes and H3K27ac changes indicating a link between CTCF binding and the activity of cis-regulatory elements (CREs). Using high-resolution Hi-C, we assessed the impact of differential CTCF binding on chromatin structure, characterizing considerable 3D genome reorganization at gene loci with perturbed CTCF peaks. Unexpectedly, we find the most drastic examples of reorganization within TADs, at the level of enhancer-promoter loops. Then, we identified DNA methylation changes as the upstream cause of CTCF binding deregulation in our breast cancer model. Using genome-wide hypomethylating agent, we were able to partially reverse observed CTCF binding changes and the gene expression changes they induced. Our work thus identifies a pervasive DNA-methylation-guided reorganization of CTCF binding and intra-TAD structure. Such recurrent patterns of epi-mutations can provide a mechanistic explanation for shared gene deregulation in cancers
Varoquaux, Nelle. "Inférence de la structure tri-dimensionnelle du génome." Thesis, Paris, ENMP, 2015. http://www.theses.fr/2015ENMP0059/document.
Full textThe structure of DNA, chromosomes and genome organization is a topic that has fascinated the field of biology for many years. Most research focused on the one-dimensional structure of the genome, studying the linear organizations of genes and genomes and their link with gene expression and regulation, splicing, DNA methylation… Yet, spatial and temporal three-dimensional genome architecture is also thought to play an important role in many genomic functions. Chromosome conformation capture (3C) based methods, coupled with next generation sequencing (NGS), allow the measurement, in a single experiment, of genome wide physical interactions between pairs of loci, thus enabling to unravel the secrets behind 3D organization of genomes. These new technologies have paved the way towards a systematic and genome wide analysis of how DNA folds into the nucleus and opened new avenues to understanding many biological processes, such as gene regulation, DNA replication and repair, somatic copy number alterations and epigenetic changes. Yet, 3C technologies, as any new biotechnology, now poses important computational and theoretical challenges for which mathematically well grounded methods need to be developped. The first chapter is dedicated to developping a robust and accurate method to infer a 3D model of the genome from Hi-C data. Previous methods often formulated the inference as an optimization problem akin to multidimensional scaling (MDS) based on an ad hoc conversion of contact counts into euclidean wish distances. Chromosomes are modeled with a beads-on-a-string model, and the methods attempt to place the beads in a 3D euclidean space to fullfill a number of, often non convex, constraints and such that the pairwise distances between beads are as close as possible to the corresponding wish distances. These approaches rely on dubious hypotheses to convert contact counts into wish distances, challenging the accuracy of the final 3D model. Another limitation is the MDS formulation which is only intuitively motivated, and not grounded on a clear statistical model. To alleviate these problems, our method models contact counts as a Poisson distribution where the intensity is a decreasing function of the spatial distance between elements interacting. We then formulate the 3D structure inference as a maximum likelihood problem. We demonstrate that our method infers robust and stable models across resolutions and datasets. The second chapter focuses on the genome architecture of the P. falciparum, a small parasite responsible for the deadliest and most virulent form of human malaria. This project was biologically driven and aimed at understanding whether and how the 3D structure of the genome related to gene expression and regulation at different time points in the complex life cycle of the parasite. In collaboration with the Le Roch lab and the Noble lab, we built 3D models of the genome at three time points which resulted in a complex genome architecture indicative of a strong association between the spatial genome and gene expression. The last chapter tackles a very different question, also based on 3C-based data. Initially developped to probe the 3D architecture of the chromosomes, Hi-C and related techniques have recently been re-purposed for diverse applications: de novo genome assembly, deconvolution of metagenomic samples and genome annotations. We describe in this chapter a novel method, Centurion, that jointly infers the locations of all centromeres in a single yeast genome from Hi-C data, using the centromeres' tendency to strongly colocalize in the nucleus. Indeed, centromeres are essential for proper chromosome segregation, yet, despite extensive research, centromere locations are unknown for many yeast species. We demonstrate the robustness of our approach on datasets with low and high coverage on well annotated organisms. We then predict centromere coordinates for 6 yeast species that currently lack those annotations
Svensson, Niclas. "Structure from Motion with Unstructured RGBD Data." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302553.
Full textFöljande examensarbete behandlar ämnet djupassisterad Struktur genom Rörelse (eng. SfM). Vid klassisk SfM är målet att återskapa en 3D scen, endast med hjälp av en sekvens av oordnade RGB bilder. I djupassiterad SfM adderas djupinformationen till problemformulering och följaktligen har ett system som kan motta RGBD bilder skapats. Problemet har lösts genom att modifiera en befintlig SfM- mjukvara och mer specifikt dess Buntjustering (eng. BA). Resultatet från den modifierade mjukvaran jämförs med resultatet av originalutgåvan för att dra slutsatser rådande modifikationens påverkan på prestandan. Resultaten visar huvudsakligen två saker. Först och främst, den modifierade mjukvaran producerar resultat med högre noggrannhet i de allra flesta fall. Skillnaden är som allra störst när bilderna är tagna från endast en liten sektor som omringar scenen. Data med brus kan dock försämra systemets prestanda aningen jämfört med orginalsystemet. För det andra, så minskar exekutionstiden betydligt. Slutligen diskuteras hur mjukvaran kan vidareutvecklas för att ytterligare förbättra resultaten.
Votroubek, Lukáš. "Webový server pro predikci 3D struktury proteinu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2013. http://www.nusl.cz/ntk/nusl-236225.
Full textBerselli, Michele. "Development and Application of Informatics Tools for the Detection and Analysis of Non-Canonical DNA Structures." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3425749.
Full textLa doppia elica del DNA è una molecola molto flessibile ed eterogenea, che può adottare una vasta gamma di conformazioni locali alternative. Queste conformazioni vengono collettivamente chiamate non-B DNA. Questi conformeri sembrano svolgere un ruolo importante in diverse condizioni cellulari sia fisiologiche che patologiche, ed influenzano molte proprietà biochimiche del genoma. La formazione di queste strutture dipende da caratteristiche specifiche della sequenza del DNA, e diversi motivi di sequenza possono portare alla formazione di diverse strutture non-B DNA. Durante questi anni, ho concentrato il mio lavoro sullo sviluppo di nuovi strumenti computazionali per la rilevazione di alcuni di questi motivi su scala genomica. Questo investimento di tempo è stato necessario, poiché attualmente mancano strumenti sufficientemente flessibili in grado di eseguire tali analisi. In particolare, mi sono concentrato sul rilevamento di motivi degenerati. A tale scopo, ho sviluppato NeSSie e QPARSE. NeSSie è in grado di rilevare in modo efficiente ed esauriente sequenze con proprietà simmetriche, come motivi speculari e palindromici associati alla formazione di forcine, strutture cruciformi e regioni di DNA a triplo filamento. QPARSE può rilevare ripetizioni consecutive di isole di G esatte o degenerate, che sono coinvolte nella formazione di G-quadruplex (G4) e strutture G-quadruplex appaiate (cioè due strutture quadruplex che si trovano vicine lungo la sequenza e che possono interagire formando una struttura di ordine superiore ed influenzandosi reciprocamente nel ripiegamento). Ho quindi iniziato a utilizzare questi strumenti per eseguire analisi su genomi appartenenti a specie di micobatterio e sul genoma umano. Nei genomi delle specie di micobatteri che sono in grado di sviluppare malattie simili alla tubercolosi, NeSSie ha rivelato l'arricchimento di un motivo con una perfetta simmetria a specchio. Analisi sperimentali hanno quindi confermato che questo motivo può piegarsi in una struttura a forcina precedentemente sconosciuta ma molto stabile. Nel genoma umano, mi sono concentrato sul rilevamento di sistemi G-quadruplex accoppiati. Una analisi su tutto il genoma ha rivelato un sorprendente arricchimento di sequenze potenzialmente coinvolte nella formazione di questi sistemi in corrispondenza del TSS (Sito di inizio della trascrizione) di migliaia di geni umani. Tra i sistemi predetti, uno identificato in corrispondenza del TSS di BCL2 è in corso di validazione sperimentale e i risultati preliminari sono promettenti. Questi risultati contribuiscono all'idea che i non-B DNA possano svolgere importanti ruoli funzionali e potenzialmente strutturali. Suggeriscono anche che il panorama di strutture che possono formarsi nella molecola di DNA sia molto più complesso di quanto ipotizzato, e che abbiamo ancora un'enorme mancanza di conoscenza verso queste strutture alternative. Seguendo queste evidenze, la sequenza del DNA deve essere ampiamente rivalutata non solo dal punto di vista della codifica, ma considerando anche le sue proprietà strutturali e funzionali. È quindi necessario indirizzare gli sforzi verso nuovi campi di indagine, studiando e caratterizzando queste strutture a livello genomico.
Manoharan, Malini. "Genomic, structural and functional characterization of odorant binding proteins in olfaction of mosquitoes involved in infectious disease transmission." Phd thesis, Université de la Réunion, 2011. http://tel.archives-ouvertes.fr/tel-00979587.
Full textMatala, Ilunga Benjamin. "Une correction à l’échelle et progressive des données Hi-C révèlent des principes fondamentaux de l’organisation tridimensionnelle et fonctionnelle du génome." Thèse, 2016. http://hdl.handle.net/1866/18662.
Full textOver the last decade, accumulating empirical evidence suggest that, as much as its sequence, a genome spatiotemporal organization is essential to understand it’s biological function. One of the major breakthroughs has been chromosome conformation capture (3C) experiments presenting DNA-DNA contact for whole genomes at unprecedented resolution (5-10kb). Along with genome-wide maps of DNA contacts came genome 3D modelling from experimental 3C data, and even from purely theoretical and biophysical basis. However, the mechanisms underlying the regulation of the genome spatial functional organization are still not well understood. Among other questions, how the regulation and event of nuclear processes such as transcription modulate genome structure or how genome structure affect these in turn is still not fully resolved. Moreover, computational models of S.cerevisae genome have recapitulated the hallmarks at larger scale of its 3D features. In order to contrast genome structural features arising from the event of biochemical and molecular activity, we have develop a method assessing the significance of structural features. The underlying principle is to consider for a given interaction, the two DNA regions put in contact and the distribution of existing interactions between these before assigning significance to the selected interaction. Using this method, we demonstrate that structural features resulting from potential biochemically active processes occur at precise scale on the genome. Our results also highlight that exact nature of the interaction (between vs across chromosomes) is crucial to such events. Finally, we have also found that a large portion of transcription factors have their targeted genes in spatial proximity.
Books on the topic "3D genome structure"
Tiana, Guido, and Luca Giorgetti. Modeling the 3D Conformation of Genomes. Taylor & Francis Group, 2019.
Find full textTiana, Guido, and Luca Giorgetti. Modeling the 3D Conformation of Genomes. Taylor & Francis Group, 2019.
Find full textThe connection of brains theory: Brain,brain waves,mind,physiology of brain,cosmic memory,humanaly memory,unlimited memory,limited memory,limbic system,thalamus,hypothalamus,midbrain,cortex, cerebral cortex, cerebral cortex ,cerebellum,cerebellar cortex,neuron,neurons,gray neurons,white neuronal,CNS,think,thoughts,Nervous system,Monkey brain,Brain Animals,Animal memory,central nervous system,smart energy,intelligent energy, intelligence creation,smartness animals,physiology of thinking,the cosmic memory,thinking system,limbic system, the cerebral cortex, brain waves, Humanaly understanding, universal memory, five senses, experiences, Human Magical Talent, book "Human Magical Talent", empirical understanding, the Spherical shape of the head,Walking on two legs, structural differences of the skull, genotype of cortical neurons, cortical neurons, past experiences, see, hear, touch, Clever behaviors, up the cortical lobes of the brain, cortical lobes, cortical lobes of the brain, Fornal lobe, planning and decisions, , planning, decisions, temporal lobe, occipital lobe, deeper parts of the brain, deep processing, brain through, genetics, phenotype,genotype, the cortical lobes, cortical lobes, HMT theory, HMT, communication of brains theory, 2% difference of the genome of brain neurons, The spherical shape of the human head, grooves of the brain, grooves, Neocortex neurons, Neocortex, brain grooves, brain proteins, catecholamines, mental habits, human cognitive abilities ,mental experience , dream, Sensory receptors, Dendrit , dendritic spines, motor neurons, hippocampus, sensory dendrites, meaningful electrical pulses, brain reactions, experiences received, shape of the brain(3D oval mode), dendritic branches , brain satellite dish full of grooves, pyramidal neurons of the neocortex , Purkinje neurons, fantastic brain, fantastic mind, grooves on the surface of the brain, grooves in the cortex, mammalian brain, cognitive abilities, human brain neurons, creativity determine, animal creativity, HMT talent, Creativity in humans, science of psychology, psychology, The idea of HMT, negative thoughts, Mental Experience, the connection of the brain to cosmic memory,koorosh behzad,. https://archive.org/details/the-connection-of-brains-theory_202207: archive.org publisher, 2022.
Find full textBook chapters on the topic "3D genome structure"
Polles, Guido, Nan Hua, Asli Yildirim, and Frank Alber. "Genome Structure Calculation through Comprehensive Data Integration." In Modeling the 3D Conformation of Genomes, 253–84. Boca Raton : Taylor & Francis, 2018. | Series: Series in computational biophysics ; 4: CRC Press, 2019. http://dx.doi.org/10.1201/9781315144009-11.
Full textCasadio, R., P. Fariselli, P. L. Martelli, A. Pierleoni, I. Rossi, and G. von Heijne. "The state of the art of membrane protein structure prediction: from sequence to 3D structure." In Modern Genome Annotation, 309–26. Vienna: Springer Vienna, 2008. http://dx.doi.org/10.1007/978-3-211-75123-7_15.
Full textIvanisenko, V. A., S. S. Pintus, D. A. Grigorovich, L. N. Ivanisenko, V. A. Debelov, and A. M. Matsokin. "PDBSiteScan: A Program Searching for Functional Sites in Protein 3D Structures." In Bioinformatics of Genome Regulation and Structure, 185–92. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-7152-4_20.
Full textPapale, Andrea, and Angelo Rvosay. "Structure and Microrheology of Genome Organization: From Experiments to Physical Modeling." In Modeling the 3D Conformation of Genomes, 139–76. Boca Raton : Taylor & Francis, 2018. | Series: Series in computational biophysics ; 4: CRC Press, 2019. http://dx.doi.org/10.1201/9781315144009-7.
Full textParo, Renato, Ueli Grossniklaus, Raffaella Santoro, and Anton Wutz. "Biology of Chromatin." In Introduction to Epigenetics, 1–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68670-3_1.
Full textWang, Yubo, Yanlin Feng, Deyan Wang, and Tao Ma. "Structural Variations and 3D Structure of the Populus Genus." In Compendium of Plant Genomes, 33–41. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-50787-8_2.
Full textBenedetti, Fabrizio, Dusan Racko, Julien Dorier, and Andrzej Stasiak. "Introducing Supercoiling into Models of Chromosome Structure." In Modeling the 3D Conformation of Genomes, 115–38. Boca Raton : Taylor & Francis, 2018. | Series: Series in computational biophysics ; 4: CRC Press, 2019. http://dx.doi.org/10.1201/9781315144009-6.
Full textGherardi, Marco, Vittore Scolari, Remus Thei Dame, and Marco Cosentino Lagomarsino. "Chromosome Structure and Dynamics in Bacteria: Theory and Experiments." In Modeling the 3D Conformation of Genomes, 207–30. Boca Raton : Taylor & Francis, 2018. | Series: Series in computational biophysics ; 4: CRC Press, 2019. http://dx.doi.org/10.1201/9781315144009-9.
Full textBhowmick, Biplab Kumar. "Possibility of Uncoding Structural Organization of Genome in Rice Research: Prospects and Approaches by 3D Genome Sequencing." In Applications of Bioinformatics in Rice Research, 3–28. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3997-5_1.
Full textSætre, Glenn-Peter, and Mark Ravinet. "Sequencing the genome and beyond." In Evolutionary Genetics, 250–68. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198830917.003.0010.
Full textConference papers on the topic "3D genome structure"
"3D-,odels creation based on solid tumor." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-311.
Full textTrieu, Tuan, and Jianlin Cheng. "3D Genome Structure Modeling by Lorentzian Objective Function." In BCB '17: 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3107411.3107455.
Full text"Simulating of 3D genome data with predefined chromosomal rearrangements." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-062.
Full text"Insights into the 3D-genome organization in malaria mosquitoes." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-059.
Full text"3D-2 heterogeneous breast cancer models." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-489.
Full text"Laser 3D-modeling in research of molecular features of skin lymphatic vessels in the patients with urticaria pigmentosa." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-296.
Full text"Multi-class abdominal aortic aneurysm segmentation via 3D neural networks." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-674.
Full text"Processing of serial microscopic images for 3D reconstruction of plant tissues." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-375.
Full text"Autophagy activation in 3D-spheroid leads to the mesenchymal stem cells rejuvenation." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-623.
Full text"804 BGRS/SB-2022 Artificial intelligence (AI) of 3D MRI images for neurooncology." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-466.
Full textReports on the topic "3D genome structure"
Rafaeli, Ada, Russell Jurenka, and Chris Sander. Molecular characterisation of PBAN-receptors: a basis for the development and screening of antagonists against Pheromone biosynthesis in moth pest species. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7695862.bard.
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