AIMC Topic: Adenine

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Dual-Branch Contrastive Network with Deep Separable Convolution for Enhanced 6mA Site Identification.

Journal of chemical information and modeling
DNA N6-methyladenine (6mA) is a pivotal DNA modification integral to various biological processes, yet its exact regulatory role in eukaryotes is still unclear and controversial due to its sparsity, limitations in detection technologies, and complex ...

Predicting the risk of ibrutinib in combination with R-ICE in patients with relapsed or refractory DLBCL using explainable machine learning algorithms.

Clinical and experimental medicine
Relapsed or refractory diffuse large B-cell lymphoma (DLBCL) poses significant therapeutic challenges due to heterogeneous patient outcomes. This study aimed to evaluate the efficacy of the ibrutinib plus R-ICE regimen and to leverage explainable mac...

Predicting adenine base editing efficiencies in different cellular contexts by deep learning.

Genome biology
BACKGROUND: Adenine base editors (ABEs) enable the conversion of A•T to G•C base pairs. Since the sequence of the target locus influences base editing efficiency, efforts have been made to develop computational models that can predict base editing ou...

HD-6mAPred: a hybrid deep learning approach for accurate prediction of N6-methyladenine sites in plant species.

PeerJ
BACKGROUND: N6-methyladenine (6mA) is an important DNA methylation modification that serves a crucial function in various biological activities. Accurate prediction of 6mA sites is essential for elucidating its biological function and underlying mech...

[Determination of Nucleosides and Nucleobases in Natural, Cultured and Tissue Culture Anoectochilus roxburghii Using LC-MS].

Zhong yao cai = Zhongyaocai = Journal of Chinese medicinal materials
OBJECTIVE: To establish a method for simultaneous determination of nucleosides and nucleobases in natural, cultured and tissue culture Anoectochilus roxburghii by high performance liquid chromatography-electrospray ionization/ion trap mass spectromet...