Artykuły w czasopismach na temat „Cellular deconvolution”
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Main, Martin J., i Andrew X. Zhang. "Advances in Cellular Target Engagement and Target Deconvolution". SLAS DISCOVERY: Advancing the Science of Drug Discovery 25, nr 2 (20.01.2020): 115–17. http://dx.doi.org/10.1177/2472555219897269.
Pełny tekst źródłaMenden, Kevin, Mohamed Marouf, Sergio Oller, Anupriya Dalmia, Daniel Sumner Magruder, Karin Kloiber, Peter Heutink i Stefan Bonn. "Deep learning–based cell composition analysis from tissue expression profiles". Science Advances 6, nr 30 (lipiec 2020): eaba2619. http://dx.doi.org/10.1126/sciadv.aba2619.
Pełny tekst źródłaSosina, Olukayode A., Matthew N. Tran, Kristen R. Maynard, Ran Tao, Margaret A. Taub, Keri Martinowich, Stephen A. Semick i in. "Strategies for cellular deconvolution in human brain RNA sequencing data". F1000Research 10 (4.08.2021): 750. http://dx.doi.org/10.12688/f1000research.50858.1.
Pełny tekst źródłaDiaz, Michael, Jasmine Tran, Nicole Natarelli, Akash Sureshkumar i 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, nr 6 (13.11.2023): 1170–73. http://dx.doi.org/10.25251/skin.7.6.15.
Pełny tekst źródłaKim, Boyoung. "DVDeconv: An Open-Source MATLAB Toolbox for Depth-Variant Asymmetric Deconvolution of Fluorescence Micrographs". Cells 10, nr 2 (15.02.2021): 397. http://dx.doi.org/10.3390/cells10020397.
Pełny tekst źródłaTurner, J. N., B. Roysam, T. J. Holmes, D. H. Szarowski, W. Lin, S. Bhattacharyya, H. Ancin, R. Mackin i 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.
Pełny tekst źródłaAbbas, Alexander R., Kristen Wolslegel, Dhaya Seshasayee i 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.
Pełny tekst źródłaUdpa, L., V. M. Ayres, Yuan Fan, Qian Chen i S. A. Kumar. "Deconvolution of atomic force microscopy data for cellular and molecular imaging". IEEE Signal Processing Magazine 23, nr 3 (maj 2006): 73–83. http://dx.doi.org/10.1109/msp.2006.1628880.
Pełny tekst źródłaBlum, Yuna, Marie-Claude Jaurand, Aurélien De Reyniès i Didier Jean. "Unraveling the cellular heterogeneity of malignant pleural mesothelioma through a deconvolution approach". Molecular & Cellular Oncology 6, nr 4 (7.05.2019): 1610322. http://dx.doi.org/10.1080/23723556.2019.1610322.
Pełny tekst źródłaPoirier, Christopher C., Win Pin Ng, Douglas N. Robinson i Pablo A. Iglesias. "Deconvolution of the Cellular Force-Generating Subsystems that Govern Cytokinesis Furrow Ingression". PLoS Computational Biology 8, nr 4 (26.04.2012): e1002467. http://dx.doi.org/10.1371/journal.pcbi.1002467.
Pełny tekst źródłaMahon, Kerry P., Terra B. Potocky, Derek Blair, Marc D. Roy, Kelly M. Stewart, Thomas C. Chiles i Shana O. Kelley. "Deconvolution of the Cellular Oxidative Stress Response with Organelle-Specific Peptide Conjugates". Chemistry & Biology 14, nr 8 (sierpień 2007): 923–30. http://dx.doi.org/10.1016/j.chembiol.2007.07.011.
Pełny tekst źródłaAlonso-Moreda, Natalia, Alberto Berral-González, Enrique De La Rosa, Oscar González-Velasco, José Manuel Sánchez-Santos i 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, nr 13 (28.06.2023): 10765. http://dx.doi.org/10.3390/ijms241310765.
Pełny tekst źródłaQin, Yufang, Weiwei Zhang, Xiaoqiang Sun, Siwei Nan, Nana Wei, Hua-Jun Wu i Xiaoqi Zheng. "Deconvolution of heterogeneous tumor samples using partial reference signals". PLOS Computational Biology 16, nr 11 (30.11.2020): e1008452. http://dx.doi.org/10.1371/journal.pcbi.1008452.
Pełny tekst źródłaMir, Mustafa, S. Derin Babacan, Michael Bednarz, Minh N. Do, Ido Golding i Gabriel Popescu. "Visualizing Escherichia coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Tomography". PLoS ONE 7, nr 6 (28.06.2012): e39816. http://dx.doi.org/10.1371/journal.pone.0039816.
Pełny tekst źródłaAbbas, Alexander R., Kristen Wolslegel, Dhaya Seshasayee, Zora Modrusan i Hilary F. Clark. "Deconvolution of Blood Microarray Data Identifies Cellular Activation Patterns in Systemic Lupus Erythematosus". PLoS ONE 4, nr 7 (1.07.2009): e6098. http://dx.doi.org/10.1371/journal.pone.0006098.
Pełny tekst źródłaMarquardt, Jens U. "Deconvolution of the cellular origin in hepatocellular carcinoma: Hepatocytes take the center stage". Hepatology 64, nr 4 (27.07.2016): 1020–23. http://dx.doi.org/10.1002/hep.28671.
Pełny tekst źródłaRosasco, Mario G., Chi-Sing Ho, Tianyou Luo, Michelle M. Stein, Luca Lonini, Martin C. Stumpe, Jagadish Venkataraman, Sonal Khare i Ameen A. Salahudeen. "Abstract 4692: Comparison of interassay similarity and cellular deconvolution in spatial transcriptomics data using Visum CytAssist". Cancer Research 83, nr 7_Supplement (4.04.2023): 4692. http://dx.doi.org/10.1158/1538-7445.am2023-4692.
Pełny tekst źródłaFisher, Cody, Jordan Krull, Aditya Bhagwate, Kerryl Greenwood-Quaintance, Matthew P. Abdel i Robin Patel. "Predicted Cellularity using RNASeq-Based Cellular Deconvolution Differentiates Periprosthetic Joint Infection from Non-Infectious Arthroplasty Failure". Journal of Immunology 208, nr 1_Supplement (1.05.2022): 170.28. http://dx.doi.org/10.4049/jimmunol.208.supp.170.28.
Pełny tekst źródłaCurtin, Lee, Kamila Bond, Sebastian Velez, Andrea Hawkins-Daarud, Javier C. Urcuyo, Gustavo De Leon, Jazlynn Langworthy i in. "BULK RNA-SEQ DECONVOLUTION OF IMAGE-LOCALIZED HIGGRADE GLIOMA BIOPSIES REVEALS MEANINGFUL CELLULAR STATES". Neuro-Oncology 25, Supplement_3 (16.09.2023): iii2. http://dx.doi.org/10.1093/neuonc/noad147.005.
Pełny tekst źródłaShah, Nameeta, Hyun Jung Park, Pranali Sonpatki, Kyung Yeon Han, Hyeon Jong Yu, Shin Wook Kim, Tamrin Chowdhury i in. "TMIC-20. A SPATIALLY RESOLVED HUMAN GLIOBLASTOMA ATLAS REVEALS DISTINCT CELLULAR AND MOLECULAR PATTERNS OF ANATOMICAL NICHES". Neuro-Oncology 25, Supplement_5 (1.11.2023): v282. http://dx.doi.org/10.1093/neuonc/noad179.1086.
Pełny tekst źródłaBornot, Aurelie, Carolyn Blackett, Ola Engkvist, Clare Murray i Claus Bendtsen. "The Role of Historical Bioactivity Data in the Deconvolution of Phenotypic Screens". Journal of Biomolecular Screening 19, nr 5 (17.01.2014): 696–706. http://dx.doi.org/10.1177/1087057113518966.
Pełny tekst źródłaHendriksen, Josephine, Aidan Flynn, Simone Maarup, Hans Poulsen, Ulrik Lassen i Joachim Weischenfeldt. "TAMI-68. DECONVOLUTION OF IMMUNOTHERAPY-TREATED GLIOBLASTOMA IDENTIFIES CELLULAR HETEROGENEITY AND PLASTICITY AT THE SINGLE-CELL LEVEL". Neuro-Oncology 23, Supplement_6 (2.11.2021): vi212. http://dx.doi.org/10.1093/neuonc/noab196.850.
Pełny tekst źródłaHendriksen, J. D., A. Flynn, S. B. Maarup, H. S. Poulsen, U. Lassen i 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 (1.09.2022): ii37. http://dx.doi.org/10.1093/neuonc/noac174.125.
Pełny tekst źródłaMorilla, Ian, i Juan A. Ranea. "Mathematical deconvolution uncovers the genetic regulatory signal of cancer cellular heterogeneity on resistance to paclitaxel". Molecular Genetics and Genomics 292, nr 4 (6.04.2017): 857–69. http://dx.doi.org/10.1007/s00438-017-1316-2.
Pełny tekst źródłaWang, Linghua. "Developmental Deconvolution Suggests New Tumor Biology and a Tool for Predicting Cancer Origin". Cancer Discovery 12, nr 11 (2.11.2022): 2498–500. http://dx.doi.org/10.1158/2159-8290.cd-22-0943.
Pełny tekst źródłaChu, Tinyi, Edward Rice, Hans Salamanca, Zhong Wang, Sharon Longo, Robert Corona, Mariano Viapiano, Lawrence Chin i Charles Danko. "COMP-14. MOLECULAR PROFILING AND CELLULAR DECONVOLUTION OF GLIOBLASTOMA BRAIN TUMORS USING CHROMATIN RUN-ON AND SEQUENCING". Neuro-Oncology 21, Supplement_6 (listopad 2019): vi64. http://dx.doi.org/10.1093/neuonc/noz175.257.
Pełny tekst źródłaVallania, Francesco, Karen Assayag, Peter Ulz, Adam Drake, Hayley Warsinske, John St John, Girish Putcha i in. "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, nr 15_suppl (20.05.2020): 9588. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.9588.
Pełny tekst źródłaWang, Kun, Sushant Patkar, Joo Sang Lee, E. Michael Gertz, Welles Robinson, Fiorella Schischlik, David R. Crawford, Alejandro A. Schäffer i 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, nr 4 (4.01.2022): 1088–105. http://dx.doi.org/10.1158/2159-8290.cd-21-0887.
Pełny tekst źródłaMahoney, Rebecca, Cathal Seoighe i Derek W. Morris. "2. USING CELLULAR DECONVOLUTION TO INVESTIGATE CELL SUBTYPE PROPORTIONS IN CORTICAL GENE EXPRESSION DATA IN SCHIZOPHRENIA". European Neuropsychopharmacology 51 (październik 2021): e41. http://dx.doi.org/10.1016/j.euroneuro.2021.07.095.
Pełny tekst źródłaHåkanson, Maria, Stefan Kobel, Matthias P. Lutolf, Marcus Textor, Edna Cukierman i Mirren Charnley. "Controlled Breast Cancer Microarrays for the Deconvolution of Cellular Multilayering and Density Effects upon Drug Responses". PLoS ONE 7, nr 6 (29.06.2012): e40141. http://dx.doi.org/10.1371/journal.pone.0040141.
Pełny tekst źródłaFriman, Tomas. "Mass spectrometry-based Cellular Thermal Shift Assay (CETSA®) for target deconvolution in phenotypic drug discovery". Bioorganic & Medicinal Chemistry 28, nr 1 (styczeń 2020): 115174. http://dx.doi.org/10.1016/j.bmc.2019.115174.
Pełny tekst źródłaKirita, Yuhei, Haojia Wu, Kohei Uchimura, Parker C. Wilson i Benjamin D. Humphreys. "Cell profiling of mouse acute kidney injury reveals conserved cellular responses to injury". Proceedings of the National Academy of Sciences 117, nr 27 (22.06.2020): 15874–83. http://dx.doi.org/10.1073/pnas.2005477117.
Pełny tekst źródłaHara, Toshiro, Rony Chanoch-Myers, Nathan Mathewson, Chad Myskiw, Lyla Atta, Lillian Bussema, Stephen Eichhorn i in. "TAMI-12. CANCER-IMMUNE CELL INTERACTIONS DRIVE TRANSITIONS TO MESENCHYMAL-LIKE STATES IN GLIOBLASTOMA". Neuro-Oncology 23, Supplement_6 (2.11.2021): vi200. http://dx.doi.org/10.1093/neuonc/noab196.796.
Pełny tekst źródłaLAI, DARONG, HONGTAO LU, MARIO LAURIA, DIGEO DI BERNARDO i CHRISTINE NARDINI. "MANIA: A GENE NETWORK REVERSE ALGORITHM FOR COMPOUNDS MODE-OF-ACTION AND GENES INTERACTIONS INFERENCE". Advances in Complex Systems 13, nr 01 (luty 2010): 83–94. http://dx.doi.org/10.1142/s0219525910002451.
Pełny tekst źródłaDilip, Deepika, Pallavi Galera, David Nemirovsky, Morgan Lallo, Kamal Menghrajani, Andriy Derkach, Ross L. Levine, Richard Koche, Wenbin Xiao i 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 (28.11.2023): 4324. http://dx.doi.org/10.1182/blood-2023-188871.
Pełny tekst źródłaFriedrich, Johannes, Pengcheng Zhou i Liam Paninski. "Fast online deconvolution of calcium imaging data". PLOS Computational Biology 13, nr 3 (14.03.2017): e1005423. http://dx.doi.org/10.1371/journal.pcbi.1005423.
Pełny tekst źródłaPatel, Riya Jayesh, Spencer Rosario, Sahithi Sonti, Ankita Kapoor, Deepak Vadehra, Sarbajit Mukherjee, Kannan Thanikachalam i Renuka V. Iyer. "Genomic predictors of sensitivity to chemotherapy and immunotherapy in cholangiocarcinoma." Journal of Clinical Oncology 42, nr 3_suppl (20.01.2024): 540. http://dx.doi.org/10.1200/jco.2024.42.3_suppl.540.
Pełny tekst źródłaMukashyaka, Patience, Pooja Kumar, David J. Mellert, Shadae Nicholas, Javad Noorbakhsh, Mattia Brugiolo, Olga Anczukow, Edison T. Liu i Jeffrey H. Chuang. "Abstract A032: Cellos: High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology". Cancer Research 84, nr 3_Supplement_2 (1.02.2024): A032. http://dx.doi.org/10.1158/1538-7445.canevol23-a032.
Pełny tekst źródłaGuo, Shuai, Xuesen Cheng, Andrew Koval, Shuangxi Ji, Qingnan Liang, Yumei Li, Leah A. Owen i in. "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, nr 7_Supplement (4.04.2023): 4273. http://dx.doi.org/10.1158/1538-7445.am2023-4273.
Pełny tekst źródłaNishikawa, Toui, Masatoshi Lee i Masataka Amau. "New generative methods for single-cell transcriptome data in bulk RNA sequence deconvolution". Scientific Reports 14, nr 1 (20.02.2024). http://dx.doi.org/10.1038/s41598-024-54798-z.
Pełny tekst źródłaZhang, Zheyang, i Jialiang Huang. "Cellular deconvolution with continuous transitions". Nature Computational Science, 13.07.2023. http://dx.doi.org/10.1038/s43588-023-00489-0.
Pełny tekst źródłaCai, Manqi, Molin Yue, Tianmeng Chen, Jinling Liu, Erick Forno, Xinhua Lu, Timothy Billiar i in. "Robust and accurate estimation of cellular fraction from tissue omics data via ensemble deconvolution". Bioinformatics, 19.04.2022. http://dx.doi.org/10.1093/bioinformatics/btac279.
Pełny tekst źródłaCroxford, Matthew, Michael Elbaum, Muthuvel Arigovindan, Zvi Kam, David Agard, Elizabeth Villa i John Sedat. "Entropy-regularized deconvolution of cellular cryotransmission electron tomograms". Proceedings of the National Academy of Sciences 118, nr 50 (7.12.2021). http://dx.doi.org/10.1073/pnas.2108738118.
Pełny tekst źródłaVellame, Dorothea Seiler, Gemma Shireby, Ailsa MacCalman, Emma L. Dempster, Joe Burrage, Tyler Gorrie-Stone, Leonard S. Schalkwyk, Jonathan Mill i Eilis Hannon. "Uncertainty quantification of reference-based cellular deconvolution algorithms". Epigenetics, 20.12.2022, 1–15. http://dx.doi.org/10.1080/15592294.2022.2137659.
Pełny tekst źródłaBell-Glenn, Shelby, Jeffrey A. Thompson, Lucas A. Salas i 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 (21.03.2022). http://dx.doi.org/10.3389/fbinf.2022.835591.
Pełny tekst źródłaHannon, Eilis, Emma L. Dempster, Jonathan P. Davies, Barry Chioza, Georgina E. T. Blake, Joe Burrage, Stefania Policicchio i in. "Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles". BMC Biology 22, nr 1 (25.01.2024). http://dx.doi.org/10.1186/s12915-024-01827-y.
Pełny tekst źródłaKwon, Yong-Jun, Hi Chul Kim, Nam Youl Kim, Seo Yeon Choi, Sungyong Jung i Auguste Genovesio. "High content cellular microarray for automated drug target deconvolution". BMC Proceedings 5, S1 (10.01.2011). http://dx.doi.org/10.1186/1753-6561-5-s1-p76.
Pełny tekst źródłaSutton, Gavin J., Daniel Poppe, Rebecca K. Simmons, Kieran Walsh, Urwah Nawaz, Ryan Lister, Johann A. Gagnon-Bartsch i Irina Voineagu. "Comprehensive evaluation of deconvolution methods for human brain gene expression". Nature Communications 13, nr 1 (15.03.2022). http://dx.doi.org/10.1038/s41467-022-28655-4.
Pełny tekst źródłaCai, Manqi, Jingtian Zhou, Chris McKennan i Jiebiao Wang. "scMD facilitates cell type deconvolution using single-cell DNA methylation references". Communications Biology 7, nr 1 (2.01.2024). http://dx.doi.org/10.1038/s42003-023-05690-5.
Pełny tekst źródłaBagka, Meropi, Hyeonyi Choi, Margaux Héritier, Hanna Schwaemmle, Quentin T. L. Pasquer, Simon M. G. Braun, Leonardo Scapozza, Yibo Wu i Sascha Hoogendoorn. "Targeted protein degradation reveals BET bromodomains as the cellular target of Hedgehog pathway inhibitor-1". Nature Communications 14, nr 1 (1.07.2023). http://dx.doi.org/10.1038/s41467-023-39657-1.
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