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Axial resolution post-processing engineering in Fresnel incoherent correlation holography

Shivasubramanian Gopinath, Joseph Rosen, Vijayakumar Anand • JPhys Photonics (2026)

Fresnel incoherent correlation holography (FINCH) is a self-interference-based incoherent digital holography method. In FINCH, light from an object point is split into two beams, modulated differently using two lenses with different focal d...

DOAJ Open Access (DOAJ) DOI: 10.1088/2515-7647/ae38ae

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

Ariel A. Hippen, Dalia K. Omran, Lukas M. Weber, Euihye Jung et al. • Genome Biology (2023)

Abstract Background Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13059-023-03077-7

On the correspondence between the transcriptomic response of a compound and its effects on its targets

Chloe Engler Hart, Daniel Ence, David Healey, Daniel Domingo-Fernández • BMC Bioinformatics (2023)

Abstract Better understanding the transcriptomic response produced by a compound perturbing its targets can shed light on the underlying biological processes regulated by the compound. However, establishing the relationship between the indu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-023-05337-6

Advances and perspectives for receiver function imaging of the Earth's internal discontinuities and velocity structures

Ling Chen, Xu Wang, Xin Wang, Zigen Wei et al. • 地球与行星物理论评 (2022)

Studying the structures, properties and origins of the Earth's internal discontinuities is an important part in the efforts to understand the physical and chemical properties of the layered Earth, as well as to explore the dynamic processes...

DOAJ Open Access (DOAJ) DOI: 10.19975/j.dqyxx.2022-029

High-fidelity single-frame computational super-resolution using signal-preserving denoising-enabled deconvolution

Fudong Xue, Lin Yuan, Wenting He, Zuo’ang Xiang et al. • Nature Communications (2026)

Abstract Computational super-resolution (SR) methods enable nanoscale imaging from single-frame wide-field or spinning-disk confocal images without hardware modifications, yet face limitations: statistical restoration suffers from noise and...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-026-70791-8

Deep learning for denoising

Siwei Yu, Jianwei Ma, Wenlong Wang • Geophysics (2019)

ABSTRACT Compared with traditional seismic noise attenuation algorithms that depend on signal models and their corresponding prior assumptions, removing noise with a deep neural network is trained based on a large training set in which the ...

OPENALEX Open Access DOI: https://doi.org/10.1190/geo2018-0668.1

Machine learning and its applications: A review

Sheena Angra, Sachin Ahuja • International Conference on Big Data Analytics and Computational Intelligence (ICBDAC) (2017)

Nowadays, large amount of data is available everywhere. Therefore, it is very important to analyze this data in order to extract some useful information and to develop an algorithm based on this analysis. This can be achieved through data m...

OPENALEX DOI: https://doi.org/10.1109/icbdaci.2017.8070809