日期 影响因子
日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:
–

Poly(vinyl chloride)/Nanocarbon Composites for Advanced Potentiometric Membrane Sensor Design

用于先进电位膜传感器设计的聚氯乙烯/纳米碳复合材料

期刊:International Journal of Molecular Sciences
影响因子:4.9
doi:10.3390/ijms25021124
Zhizhin, Konstantin Yu; Turyshev, Evgeniy S; Shpigun, Liliya K; Gorobtsov, Philipp Yu; Simonenko, Nikolay P; Simonenko, Tatiana L; Kuznetsov, Nikolay T
发表日期：2024
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Molecular Dynamics Simulation Study of the Self-Assembly of Phenylalanine Peptide Nanotubes

苯丙氨酸肽纳米管自组装的分子动力学模拟研究

期刊:Nanomaterials
影响因子:4.3
doi:10.3390/nano12050861
Bystrov, Vladimir; Likhachev, Ilya; Sidorova, Alla; Filippov, Sergey; Lutsenko, Aleksey; Shpigun, Denis; Belova, Ekaterina
发表日期：2022
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Analysis of Primary Liquid Chromatography Mass Spectrometry Data by Neural Networks for Plant Samples Classification

利用神经网络分析初级液相色谱质谱数据进行植物样品分类

期刊:Metabolites
影响因子:3.4
doi:10.3390/metabo12100993
Polina Turova, Andrey Stavrianidi, Viktor Svekolkin, Dmitry Lyskov, Ilya Podolskiy, Igor Rodin, Oleg Shpigun, Aleksey Buryak
神经
发表日期：2022
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Quantitative Assessment of Chirality of Protein Secondary Structures and Phenylalanine Peptide Nanotubes

蛋白质二级结构和苯丙氨酸肽纳米管手性的定量评估

期刊:Nanomaterials
影响因子:4.3
doi:10.3390/nano11123299
Sidorova, Alla; Bystrov, Vladimir; Lutsenko, Aleksey; Shpigun, Denis; Belova, Ekaterina; Likhachev, Ilya
发表日期：2021
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Modeling of Self-Assembled Peptide Nanotubes and Determination of Their Chirality Sign Based on Dipole Moment Calculations

基于偶极矩计算的自组装肽纳米管建模及其手性符号确定

期刊:Nanomaterials
影响因子:4.3
doi:10.3390/nano11092415
Bystrov, Vladimir; Sidorova, Alla; Lutsenko, Aleksey; Shpigun, Denis; Malyshko, Ekaterina; Nuraeva, Alla; Zelenovskiy, Pavel; Kopyl, Svitlana; Kholkin, Andrei
发表日期：2021
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A New Electrochemical Sensor for Direct Detection of Purine Antimetabolites and DNA Degradation

一种用于直接检测嘌呤抗代谢物和DNA降解的新型电化学传感器

期刊:Journal of Analytical Methods in Chemistry
影响因子:2.2
doi:10.1155/2019/1572526
Shpigun, Liliya K; Andryukhina, Elena Yu
代谢
发表日期：2019
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Employing fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task

利用液相色谱-质谱联用技术（LC-MS）和机器学习对药用植物进行指纹图谱分析，以完成物种鉴定任务。

期刊:Scientific Reports
影响因子:3.9
doi:10.1038/s41598-018-35399-z
Kharyuk, Pavel; Nazarenko, Dmitry; Oseledets, Ivan; Rodin, Igor; Shpigun, Oleg; Tsitsilin, Andrey; Lavrentyev, Mikhail
多发性硬化症
发表日期：2018
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