Artículos de revistas sobre el tema "Cellular deconvolution"
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Main, Martin J. y Andrew X. Zhang. "Advances in Cellular Target Engagement and Target Deconvolution". SLAS DISCOVERY: Advancing the Science of Drug Discovery 25, n.º 2 (20 de enero de 2020): 115–17. http://dx.doi.org/10.1177/2472555219897269.
Texto completoMenden, Kevin, Mohamed Marouf, Sergio Oller, Anupriya Dalmia, Daniel Sumner Magruder, Karin Kloiber, Peter Heutink y Stefan Bonn. "Deep learning–based cell composition analysis from tissue expression profiles". Science Advances 6, n.º 30 (julio de 2020): eaba2619. http://dx.doi.org/10.1126/sciadv.aba2619.
Texto completoSosina, Olukayode A., Matthew N. Tran, Kristen R. Maynard, Ran Tao, Margaret A. Taub, Keri Martinowich, Stephen A. Semick et al. "Strategies for cellular deconvolution in human brain RNA sequencing data". F1000Research 10 (4 de agosto de 2021): 750. http://dx.doi.org/10.12688/f1000research.50858.1.
Texto completoDiaz, Michael, Jasmine Tran, Nicole Natarelli, Akash Sureshkumar y Mahtab Forouzandeh. "Cellular Deconvolution Reveals Unique Findings in Several Cell Type Fractions Within the Basal Cell Carcinoma Tumor Microenvironment". SKIN The Journal of Cutaneous Medicine 7, n.º 6 (13 de noviembre de 2023): 1170–73. http://dx.doi.org/10.25251/skin.7.6.15.
Texto completoKim, Boyoung. "DVDeconv: An Open-Source MATLAB Toolbox for Depth-Variant Asymmetric Deconvolution of Fluorescence Micrographs". Cells 10, n.º 2 (15 de febrero de 2021): 397. http://dx.doi.org/10.3390/cells10020397.
Texto completoTurner, J. N., B. Roysam, T. J. Holmes, D. H. Szarowski, W. Lin, S. Bhattacharyya, H. Ancin, R. Mackin y D. Becker. "Visualization and quantitation of cellular and tissue anatomy by 3D light microscopy". Proceedings, annual meeting, Electron Microscopy Society of America 52 (1994): 928–29. http://dx.doi.org/10.1017/s0424820100172371.
Texto completoAbbas, Alexander R., Kristen Wolslegel, Dhaya Seshasayee y Hilary F. Clark. "Deconvolution of Blood Microarray Data Elucidates Cellular Activation Patterns in SLE". Clinical Immunology 123 (2007): S125—S126. http://dx.doi.org/10.1016/j.clim.2007.03.536.
Texto completoUdpa, L., V. M. Ayres, Yuan Fan, Qian Chen y S. A. Kumar. "Deconvolution of atomic force microscopy data for cellular and molecular imaging". IEEE Signal Processing Magazine 23, n.º 3 (mayo de 2006): 73–83. http://dx.doi.org/10.1109/msp.2006.1628880.
Texto completoBlum, Yuna, Marie-Claude Jaurand, Aurélien De Reyniès y Didier Jean. "Unraveling the cellular heterogeneity of malignant pleural mesothelioma through a deconvolution approach". Molecular & Cellular Oncology 6, n.º 4 (7 de mayo de 2019): 1610322. http://dx.doi.org/10.1080/23723556.2019.1610322.
Texto completoPoirier, Christopher C., Win Pin Ng, Douglas N. Robinson y Pablo A. Iglesias. "Deconvolution of the Cellular Force-Generating Subsystems that Govern Cytokinesis Furrow Ingression". PLoS Computational Biology 8, n.º 4 (26 de abril de 2012): e1002467. http://dx.doi.org/10.1371/journal.pcbi.1002467.
Texto completoMahon, Kerry P., Terra B. Potocky, Derek Blair, Marc D. Roy, Kelly M. Stewart, Thomas C. Chiles y Shana O. Kelley. "Deconvolution of the Cellular Oxidative Stress Response with Organelle-Specific Peptide Conjugates". Chemistry & Biology 14, n.º 8 (agosto de 2007): 923–30. http://dx.doi.org/10.1016/j.chembiol.2007.07.011.
Texto completoAlonso-Moreda, Natalia, Alberto Berral-González, Enrique De La Rosa, Oscar González-Velasco, José Manuel Sánchez-Santos y Javier De Las Rivas. "Comparative Analysis of Cell Mixtures Deconvolution and Gene Signatures Generated for Blood, Immune and Cancer Cells". International Journal of Molecular Sciences 24, n.º 13 (28 de junio de 2023): 10765. http://dx.doi.org/10.3390/ijms241310765.
Texto completoQin, Yufang, Weiwei Zhang, Xiaoqiang Sun, Siwei Nan, Nana Wei, Hua-Jun Wu y Xiaoqi Zheng. "Deconvolution of heterogeneous tumor samples using partial reference signals". PLOS Computational Biology 16, n.º 11 (30 de noviembre de 2020): e1008452. http://dx.doi.org/10.1371/journal.pcbi.1008452.
Texto completoMir, Mustafa, S. Derin Babacan, Michael Bednarz, Minh N. Do, Ido Golding y Gabriel Popescu. "Visualizing Escherichia coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Tomography". PLoS ONE 7, n.º 6 (28 de junio de 2012): e39816. http://dx.doi.org/10.1371/journal.pone.0039816.
Texto completoAbbas, Alexander R., Kristen Wolslegel, Dhaya Seshasayee, Zora Modrusan y Hilary F. Clark. "Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus". PLoS ONE 4, n.º 7 (1 de julio de 2009): e6098. http://dx.doi.org/10.1371/journal.pone.0006098.
Texto completoMarquardt, Jens U. "Deconvolution of the cellular origin in hepatocellular carcinoma: Hepatocytes take the center stage". Hepatology 64, n.º 4 (27 de julio de 2016): 1020–23. http://dx.doi.org/10.1002/hep.28671.
Texto completoRosasco, Mario G., Chi-Sing Ho, Tianyou Luo, Michelle M. Stein, Luca Lonini, Martin C. Stumpe, Jagadish Venkataraman, Sonal Khare y Ameen A. Salahudeen. "Abstract 4692: Comparison of interassay similarity and cellular deconvolution in spatial transcriptomics data using Visum CytAssist". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 4692. http://dx.doi.org/10.1158/1538-7445.am2023-4692.
Texto completoFisher, Cody, Jordan Krull, Aditya Bhagwate, Kerryl Greenwood-Quaintance, Matthew P. Abdel y Robin Patel. "Predicted Cellularity using RNASeq-Based Cellular Deconvolution Differentiates Periprosthetic Joint Infection from Non-Infectious Arthroplasty Failure". Journal of Immunology 208, n.º 1_Supplement (1 de mayo de 2022): 170.28. http://dx.doi.org/10.4049/jimmunol.208.supp.170.28.
Texto completoCurtin, Lee, Kamila Bond, Sebastian Velez, Andrea Hawkins-Daarud, Javier C. Urcuyo, Gustavo De Leon, Jazlynn Langworthy et al. "BULK RNA-SEQ DECONVOLUTION OF IMAGE-LOCALIZED HIGGRADE GLIOMA BIOPSIES REVEALS MEANINGFUL CELLULAR STATES". Neuro-Oncology 25, Supplement_3 (16 de septiembre de 2023): iii2. http://dx.doi.org/10.1093/neuonc/noad147.005.
Texto completoShah, Nameeta, Hyun Jung Park, Pranali Sonpatki, Kyung Yeon Han, Hyeon Jong Yu, Shin Wook Kim, Tamrin Chowdhury et al. "TMIC-20. A SPATIALLY RESOLVED HUMAN GLIOBLASTOMA ATLAS REVEALS DISTINCT CELLULAR AND MOLECULAR PATTERNS OF ANATOMICAL NICHES". Neuro-Oncology 25, Supplement_5 (1 de noviembre de 2023): v282. http://dx.doi.org/10.1093/neuonc/noad179.1086.
Texto completoBornot, Aurelie, Carolyn Blackett, Ola Engkvist, Clare Murray y Claus Bendtsen. "The Role of Historical Bioactivity Data in the Deconvolution of Phenotypic Screens". Journal of Biomolecular Screening 19, n.º 5 (17 de enero de 2014): 696–706. http://dx.doi.org/10.1177/1087057113518966.
Texto completoHendriksen, Josephine, Aidan Flynn, Simone Maarup, Hans Poulsen, Ulrik Lassen y Joachim Weischenfeldt. "TAMI-68. DECONVOLUTION OF IMMUNOTHERAPY-TREATED GLIOBLASTOMA IDENTIFIES CELLULAR HETEROGENEITY AND PLASTICITY AT THE SINGLE-CELL LEVEL". Neuro-Oncology 23, Supplement_6 (2 de noviembre de 2021): vi212. http://dx.doi.org/10.1093/neuonc/noab196.850.
Texto completoHendriksen, J. D., A. Flynn, S. B. Maarup, H. S. Poulsen, U. Lassen y J. Weischenfeldt. "P06.01.A Deconvolution of immunotherapy-treated glioblastoma identifies cellular heterogeneity and plasticity at the single-cell level". Neuro-Oncology 24, Supplement_2 (1 de septiembre de 2022): ii37. http://dx.doi.org/10.1093/neuonc/noac174.125.
Texto completoMorilla, Ian y Juan A. Ranea. "Mathematical deconvolution uncovers the genetic regulatory signal of cancer cellular heterogeneity on resistance to paclitaxel". Molecular Genetics and Genomics 292, n.º 4 (6 de abril de 2017): 857–69. http://dx.doi.org/10.1007/s00438-017-1316-2.
Texto completoWang, Linghua. "Developmental Deconvolution Suggests New Tumor Biology and a Tool for Predicting Cancer Origin". Cancer Discovery 12, n.º 11 (2 de noviembre de 2022): 2498–500. http://dx.doi.org/10.1158/2159-8290.cd-22-0943.
Texto completoChu, Tinyi, Edward Rice, Hans Salamanca, Zhong Wang, Sharon Longo, Robert Corona, Mariano Viapiano, Lawrence Chin y Charles Danko. "COMP-14. MOLECULAR PROFILING AND CELLULAR DECONVOLUTION OF GLIOBLASTOMA BRAIN TUMORS USING CHROMATIN RUN-ON AND SEQUENCING". Neuro-Oncology 21, Supplement_6 (noviembre de 2019): vi64. http://dx.doi.org/10.1093/neuonc/noz175.257.
Texto completoVallania, Francesco, Karen Assayag, Peter Ulz, Adam Drake, Hayley Warsinske, John St John, Girish Putcha et al. "Plasma-derived cfDNA to reveal potential biomarkers of response prediction and monitoring in non-small cell lung cancer (NSCLC) patients on immunotherapy." Journal of Clinical Oncology 38, n.º 15_suppl (20 de mayo de 2020): 9588. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.9588.
Texto completoWang, Kun, Sushant Patkar, Joo Sang Lee, E. Michael Gertz, Welles Robinson, Fiorella Schischlik, David R. Crawford, Alejandro A. Schäffer y Eytan Ruppin. "Deconvolving Clinically Relevant Cellular Immune Cross-talk from Bulk Gene Expression Using CODEFACS and LIRICS Stratifies Patients with Melanoma to Anti–PD-1 Therapy". Cancer Discovery 12, n.º 4 (4 de enero de 2022): 1088–105. http://dx.doi.org/10.1158/2159-8290.cd-21-0887.
Texto completoMahoney, Rebecca, Cathal Seoighe y Derek W. Morris. "2. USING CELLULAR DECONVOLUTION TO INVESTIGATE CELL SUBTYPE PROPORTIONS IN CORTICAL GENE EXPRESSION DATA IN SCHIZOPHRENIA". European Neuropsychopharmacology 51 (octubre de 2021): e41. http://dx.doi.org/10.1016/j.euroneuro.2021.07.095.
Texto completoHåkanson, Maria, Stefan Kobel, Matthias P. Lutolf, Marcus Textor, Edna Cukierman y Mirren Charnley. "Controlled Breast Cancer Microarrays for the Deconvolution of Cellular Multilayering and Density Effects upon Drug Responses". PLoS ONE 7, n.º 6 (29 de junio de 2012): e40141. http://dx.doi.org/10.1371/journal.pone.0040141.
Texto completoFriman, Tomas. "Mass spectrometry-based Cellular Thermal Shift Assay (CETSA®) for target deconvolution in phenotypic drug discovery". Bioorganic & Medicinal Chemistry 28, n.º 1 (enero de 2020): 115174. http://dx.doi.org/10.1016/j.bmc.2019.115174.
Texto completoKirita, Yuhei, Haojia Wu, Kohei Uchimura, Parker C. Wilson y Benjamin D. Humphreys. "Cell profiling of mouse acute kidney injury reveals conserved cellular responses to injury". Proceedings of the National Academy of Sciences 117, n.º 27 (22 de junio de 2020): 15874–83. http://dx.doi.org/10.1073/pnas.2005477117.
Texto completoHara, Toshiro, Rony Chanoch-Myers, Nathan Mathewson, Chad Myskiw, Lyla Atta, Lillian Bussema, Stephen Eichhorn et al. "TAMI-12. CANCER-IMMUNE CELL INTERACTIONS DRIVE TRANSITIONS TO MESENCHYMAL-LIKE STATES IN GLIOBLASTOMA". Neuro-Oncology 23, Supplement_6 (2 de noviembre de 2021): vi200. http://dx.doi.org/10.1093/neuonc/noab196.796.
Texto completoLAI, DARONG, HONGTAO LU, MARIO LAURIA, DIGEO DI BERNARDO y CHRISTINE NARDINI. "MANIA: A GENE NETWORK REVERSE ALGORITHM FOR COMPOUNDS MODE-OF-ACTION AND GENES INTERACTIONS INFERENCE". Advances in Complex Systems 13, n.º 01 (febrero de 2010): 83–94. http://dx.doi.org/10.1142/s0219525910002451.
Texto completoDilip, Deepika, Pallavi Galera, David Nemirovsky, Morgan Lallo, Kamal Menghrajani, Andriy Derkach, Ross L. Levine, Richard Koche, Wenbin Xiao y Jacob Glass. "Precision Lineage Deconvolution in Mixed Phenotype Acute Leukemia Using Cite-Seq Derived Hematopoietic Stages Identifies Lineage Dynamics Associated with Treatment Response". Blood 142, Supplement 1 (28 de noviembre de 2023): 4324. http://dx.doi.org/10.1182/blood-2023-188871.
Texto completoFriedrich, Johannes, Pengcheng Zhou y Liam Paninski. "Fast online deconvolution of calcium imaging data". PLOS Computational Biology 13, n.º 3 (14 de marzo de 2017): e1005423. http://dx.doi.org/10.1371/journal.pcbi.1005423.
Texto completoPatel, Riya Jayesh, Spencer Rosario, Sahithi Sonti, Ankita Kapoor, Deepak Vadehra, Sarbajit Mukherjee, Kannan Thanikachalam y Renuka V. Iyer. "Genomic predictors of sensitivity to chemotherapy and immunotherapy in cholangiocarcinoma." Journal of Clinical Oncology 42, n.º 3_suppl (20 de enero de 2024): 540. http://dx.doi.org/10.1200/jco.2024.42.3_suppl.540.
Texto completoMukashyaka, Patience, Pooja Kumar, David J. Mellert, Shadae Nicholas, Javad Noorbakhsh, Mattia Brugiolo, Olga Anczukow, Edison T. Liu y Jeffrey H. Chuang. "Abstract A032: Cellos: High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology". Cancer Research 84, n.º 3_Supplement_2 (1 de febrero de 2024): A032. http://dx.doi.org/10.1158/1538-7445.canevol23-a032.
Texto completoGuo, Shuai, Xuesen Cheng, Andrew Koval, Shuangxi Ji, Qingnan Liang, Yumei Li, Leah A. Owen et al. "Abstract 4273: Integration with benchmark data of paired bulk and single-cell RNA sequencing data substantially improves the accuracy of bulk tissue deconvolution". Cancer Research 83, n.º 7_Supplement (4 de abril de 2023): 4273. http://dx.doi.org/10.1158/1538-7445.am2023-4273.
Texto completoNishikawa, Toui, Masatoshi Lee y Masataka Amau. "New generative methods for single-cell transcriptome data in bulk RNA sequence deconvolution". Scientific Reports 14, n.º 1 (20 de febrero de 2024). http://dx.doi.org/10.1038/s41598-024-54798-z.
Texto completoZhang, Zheyang y Jialiang Huang. "Cellular deconvolution with continuous transitions". Nature Computational Science, 13 de julio de 2023. http://dx.doi.org/10.1038/s43588-023-00489-0.
Texto completoCai, Manqi, Molin Yue, Tianmeng Chen, Jinling Liu, Erick Forno, Xinhua Lu, Timothy Billiar et al. "Robust and accurate estimation of cellular fraction from tissue omics data via ensemble deconvolution". Bioinformatics, 19 de abril de 2022. http://dx.doi.org/10.1093/bioinformatics/btac279.
Texto completoCroxford, Matthew, Michael Elbaum, Muthuvel Arigovindan, Zvi Kam, David Agard, Elizabeth Villa y John Sedat. "Entropy-regularized deconvolution of cellular cryotransmission electron tomograms". Proceedings of the National Academy of Sciences 118, n.º 50 (7 de diciembre de 2021). http://dx.doi.org/10.1073/pnas.2108738118.
Texto completoVellame, Dorothea Seiler, Gemma Shireby, Ailsa MacCalman, Emma L. Dempster, Joe Burrage, Tyler Gorrie-Stone, Leonard S. Schalkwyk, Jonathan Mill y Eilis Hannon. "Uncertainty quantification of reference-based cellular deconvolution algorithms". Epigenetics, 20 de diciembre de 2022, 1–15. http://dx.doi.org/10.1080/15592294.2022.2137659.
Texto completoBell-Glenn, Shelby, Jeffrey A. Thompson, Lucas A. Salas y Devin C. Koestler. "A Novel Framework for the Identification of Reference DNA Methylation Libraries for Reference-Based Deconvolution of Cellular Mixtures". Frontiers in Bioinformatics 2 (21 de marzo de 2022). http://dx.doi.org/10.3389/fbinf.2022.835591.
Texto completoHannon, Eilis, Emma L. Dempster, Jonathan P. Davies, Barry Chioza, Georgina E. T. Blake, Joe Burrage, Stefania Policicchio et al. "Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles". BMC Biology 22, n.º 1 (25 de enero de 2024). http://dx.doi.org/10.1186/s12915-024-01827-y.
Texto completoKwon, Yong-Jun, Hi Chul Kim, Nam Youl Kim, Seo Yeon Choi, Sungyong Jung y Auguste Genovesio. "High content cellular microarray for automated drug target deconvolution". BMC Proceedings 5, S1 (10 de enero de 2011). http://dx.doi.org/10.1186/1753-6561-5-s1-p76.
Texto completoSutton, Gavin J., Daniel Poppe, Rebecca K. Simmons, Kieran Walsh, Urwah Nawaz, Ryan Lister, Johann A. Gagnon-Bartsch y Irina Voineagu. "Comprehensive evaluation of deconvolution methods for human brain gene expression". Nature Communications 13, n.º 1 (15 de marzo de 2022). http://dx.doi.org/10.1038/s41467-022-28655-4.
Texto completoCai, Manqi, Jingtian Zhou, Chris McKennan y Jiebiao Wang. "scMD facilitates cell type deconvolution using single-cell DNA methylation references". Communications Biology 7, n.º 1 (2 de enero de 2024). http://dx.doi.org/10.1038/s42003-023-05690-5.
Texto completoBagka, Meropi, Hyeonyi Choi, Margaux Héritier, Hanna Schwaemmle, Quentin T. L. Pasquer, Simon M. G. Braun, Leonardo Scapozza, Yibo Wu y Sascha Hoogendoorn. "Targeted protein degradation reveals BET bromodomains as the cellular target of Hedgehog pathway inhibitor-1". Nature Communications 14, n.º 1 (1 de julio de 2023). http://dx.doi.org/10.1038/s41467-023-39657-1.
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