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41,899 results

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Page 1
Dimensionality reduction approach for many-objective epistasis analysis.
Yang CH, Hou MF, Chuang LY, Yang CS, Lin YD. Yang CH, et al. Brief Bioinform. 2023 Jan 19;24(1):bbac512. doi: 10.1093/bib/bbac512. Brief Bioinform. 2023. PMID: 36458451 Free article.
Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results indicating that two objective functions could enhance SSI identification with weak marginal effects. ...In total, 6 disease models with and 40 …
Our previous study proposed a multiobjective approach-based multifactor dimensionality reduction (MOMDR), with the results ind …
Dimensionality Reduction of Single-Cell RNA-Seq Data.
Linderman GC. Linderman GC. Methods Mol Biol. 2021;2284:331-342. doi: 10.1007/978-1-0716-1307-8_18. Methods Mol Biol. 2021. PMID: 33835451
Dimensionality reduction is a crucial step in essentially every single-cell RNA-sequencing (scRNA-seq) analysis. In this chapter, we describe the typical dimensionality reduction workflow that is used for scRNA-seq datasets, specifically highlighting t …
Dimensionality reduction is a crucial step in essentially every single-cell RNA-sequencing (scRNA-seq) analysis. In this chapt …
Dimensionality Reduction for Countermovement Jump Metrics.
James LP, Suppiah H, McGuigan MR, Carey DL. James LP, et al. Int J Sports Physiol Perform. 2021 Jul 1;16(7):1052-1055. doi: 10.1123/ijspp.2020-0606. Epub 2021 Mar 1. Int J Sports Physiol Perform. 2021. PMID: 33647877
The purpose of this investigation was to show how to apply dimensionality reduction to CMJ data with a view to offer practitioners solutions to aid applications in high-performance settings. METHODS: The data were collected from 3 cohorts using 3 different devices. …
The purpose of this investigation was to show how to apply dimensionality reduction to CMJ data with a view to offer practitio …
Dimensionality reduction simplifies synaptic partner matching in an olfactory circuit.
Lyu C, Li Z, Xu C, Wong KKL, Luginbuhl DJ, McLaughlin CN, Xie Q, Li T, Li H, Luo L. Lyu C, et al. Science. 2025 May;388(6746):538-544. doi: 10.1126/science.ads7633. Epub 2025 May 1. Science. 2025. PMID: 40310920 Free PMC article.
In this work, we discovered a principle that can establish the 3D glomerular map of the fly antennal lobe by reducing the higher dimensionality serially to 1D projections. During development, olfactory receptor neuron (ORN) axons first contact their partner projection neur …
In this work, we discovered a principle that can establish the 3D glomerular map of the fly antennal lobe by reducing the higher dimensio …
Sparse dimensionality reduction for analyzing single-cell-resolved interactions.
Brunn N, Hackenberg M, Fullio CL, Vogel T, Binder H. Brunn N, et al. Bioinformatics. 2024 Dec 26;5(1):vbaf230. doi: 10.1093/bioadv/vbaf230. Bioinformatics. 2024. PMID: 41092369 Free PMC article.
To enhance downstream analyses, we present an end-to-end dimensionality reduction workflow, specifically tailored for single-cell cell-cell interaction data. In particular, we demonstrate that sparse dimensionality reduction can pinpoint specific ligan …
To enhance downstream analyses, we present an end-to-end dimensionality reduction workflow, specifically tailored for single-c …
ivis Dimensionality Reduction Framework for Biomacromolecular Simulations.
Tian H, Tao P. Tian H, et al. J Chem Inf Model. 2020 Oct 26;60(10):4569-4581. doi: 10.1021/acs.jcim.0c00485. Epub 2020 Sep 1. J Chem Inf Model. 2020. PMID: 32820912 Free PMC article.
To gain more insights into the protein structure-function relations, appropriate dimensionality reduction methods are needed to project simulations onto low-dimensional spaces. Linear dimensionality reduction methods, such as principal component analys …
To gain more insights into the protein structure-function relations, appropriate dimensionality reduction methods are needed t …
Epistasis, complexity, and multifactor dimensionality reduction.
Pan Q, Hu T, Moore JH. Pan Q, et al. Methods Mol Biol. 2013;1019:465-77. doi: 10.1007/978-1-62703-447-0_22. Methods Mol Biol. 2013. PMID: 23756906 Review.
We review here computational approaches to genetic analysis that embrace, rather than ignore, the complexity of human health. We focus on multifactor dimensionality reduction (MDR) as an approach for modeling one of these complexities: epistasis or gene-gene interac …
We review here computational approaches to genetic analysis that embrace, rather than ignore, the complexity of human health. We focus on mu …
Dimensionality Reduction: Foundations and Applications in Clinical Neuroscience.
Kernbach JM, Ort J, Hakvoort K, Clusmann H, Delev D, Neuloh G. Kernbach JM, et al. Acta Neurochir Suppl. 2022;134:59-63. doi: 10.1007/978-3-030-85292-4_8. Acta Neurochir Suppl. 2022. PMID: 34862528
Different methodological approaches can be applied to alleviate the problems that arise in high-dimensional settings by reducing the original information into meaningful and concise features. One popular approach is dimensionality reduction, which allows to summariz …
Different methodological approaches can be applied to alleviate the problems that arise in high-dimensional settings by reducing the origina …
A roadmap to multifactor dimensionality reduction methods.
Gola D, Mahachie John JM, van Steen K, König IR. Gola D, et al. Brief Bioinform. 2016 Mar;17(2):293-308. doi: 10.1093/bib/bbv038. Epub 2015 Jun 24. Brief Bioinform. 2016. PMID: 26108231 Free PMC article. Review.
From this latter family, a fast-growing collection of methods emerged that are based on the Multifactor Dimensionality Reduction (MDR) approach. Since its first introduction, MDR has enjoyed great popularity in applications and has been extended and modified multipl …
From this latter family, a fast-growing collection of methods emerged that are based on the Multifactor Dimensionality Reduction …
Dimensionality reduction by UMAP reinforces sample heterogeneity analysis in bulk transcriptomic data.
Yang Y, Sun H, Zhang Y, Zhang T, Gong J, Wei Y, Duan YG, Shu M, Yang Y, Wu D, Yu D. Yang Y, et al. Cell Rep. 2021 Jul 27;36(4):109442. doi: 10.1016/j.celrep.2021.109442. Cell Rep. 2021. PMID: 34320340 Free article.
Transcriptomic analysis plays a key role in biomedical research. Linear dimensionality reduction methods, especially principal-component analysis (PCA), are widely used in detecting sample-to-sample heterogeneity, while recently developed non-linear methods, such as …
Transcriptomic analysis plays a key role in biomedical research. Linear dimensionality reduction methods, especially principal …
41,899 results
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