Výsledky vyhledávání - "Stephanie I Fraley"

Akademický článek

Insights gained from computational modeling of YAP/TAZ signaling for cellular mechanotransduction

Autor: Hamidreza Jafarinia, Ali Khalilimeybodi, Jorge Barrasa-Fano, Stephanie I. Fraley, Padmini Rangamani, Aurélie Carlier

Publikováno v: npj Systems Biology and Applications, Vol 10, Iss 1, Pp 1-14 (2024)

Abstract YAP/TAZ signaling pathway is regulated by a multiplicity of feedback loops, crosstalk with other pathways, and both mechanical and biochemical stimuli. Computational modeling serves as a powerful tool to unravel how these different factors c

Externí odkaz: https://doaj.org/article/4cafd4c724544d5596787bfcf7bcc97a

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Akademický článek

Divergent iron regulatory states contribute to heterogeneity in breast cancer aggressiveness

Autor: William D. Leineweber, Maya Z. Rowell, Sural K. Ranamukhaarachchi, Alyssa Walker, Yajuan Li, Jorge Villazon, Aida Mestre-Farrera, Zhimin Hu, Jing Yang, Lingyan Shi, Stephanie I. Fraley

Publikováno v: iScience, Vol 27, Iss 9, Pp 110661- (2024)

Summary: Contact with dense collagen I (Col1) can induce collective invasion of triple negative breast cancer (TNBC) cells and transcriptional signatures linked to poor patient prognosis. However, this response is heterogeneous and not well understoo

Externí odkaz: https://doaj.org/article/d6077827910e4b4781e32a41c68ddb5c

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Akademický článek

Machine learning based DNA melt curve profiling enables automated novel genotype detection

Autor: Aaron Boussina, Lennart Langouche, Augustine C. Obirieze, Mridu Sinha, Hannah Mack, William Leineweber, April Aralar, David T. Pride, Todd P. Coleman, Stephanie I. Fraley

Publikováno v: BMC Bioinformatics, Vol 25, Iss 1, Pp 1-13 (2024)

Abstract Surveillance for genetic variation of microbial pathogens, both within and among species, plays an important role in informing research, diagnostic, prevention, and treatment activities for disease control. However, large-scale systematic sc

Externí odkaz: https://doaj.org/article/eb1d0820ec3b437381ca816a07969730

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Akademický článek

Trainable high resolution melt curve machine learning classifier for large-scale reliable genotyping of sequence variants.

Autor: Pornpat Athamanolap, Vishwa Parekh, Stephanie I Fraley, Vatsal Agarwal, Dong J Shin, Michael A Jacobs, Tza-Huei Wang, Samuel Yang

Publikováno v: PLoS ONE, Vol 9, Iss 9, p e109094 (2014)

High resolution melt (HRM) is gaining considerable popularity as a simple and robust method for genotyping sequence variants. However, accurate genotyping of an unknown sample for which a large number of possible variants may exist will require an au

Externí odkaz: https://doaj.org/article/d7649fa0c06545d5a0c9201004aa0fc9

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Akademický článek

A simple solid media assay for detection of synergy between bacteriophages and antibiotics

Publikováno v: Microbiology Spectrum, Vol 12, Iss 5 (2024)

ABSTRACTThe emergence of antibiotic-resistant bacteria (ARB) has necessitated the development of alternative therapies to deal with this global threat. Bacteriophages (viruses that target bacteria) that kill ARB are one such alternative. Although pha

Externí odkaz: https://doaj.org/article/25057b0432e1441eaf75c77a7d0b3b37

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Akademický článek

A phenotypically supervised single-cell analysis protocol to study within-cell-type heterogeneity of cultured mammalian cells

Autor: Kevin Chen, Kivilcim Ozturk, Ted Liefeld, Michael Reich, Jill P. Mesirov, Hannah Carter, Stephanie I. Fraley

Publikováno v: STAR Protocols, Vol 2, Iss 2, Pp 100561- (2021)

Summary: Here, we describe a protocol combining functional metrics with genomic data to elucidate drivers of within-cell-type heterogeneity via the phenotype-to-genotype link. This technique involves using fluorescence tagging to label and isolate ce

Externí odkaz: https://doaj.org/article/fee7bbc3ad4b4134803a0ffe4b08a95f

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Akademický článek

Phenotypically supervised single-cell sequencing parses within-cell-type heterogeneity

Autor: Kevin Chen, Kivilcim Ozturk, Ryne L. Contreras, Jessica Simon, Sean McCann, Wei Ji Chen, Hannah Carter, Stephanie I. Fraley

Publikováno v: iScience, Vol 24, Iss 1, Pp 101991- (2021)

Summary: To better understand cellular communication driving diverse behaviors, we need to uncover the molecular mechanisms of within-cell-type functional heterogeneity. While single-cell RNA sequencing (scRNAseq) has advanced our understanding of ce

Externí odkaz: https://doaj.org/article/3e4cd35c6b7f448ab3af24a03a3e2d3a

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