Ying Ju

2.3k total citations · 2 hit papers
33 papers, 1.8k citations indexed

About

Ying Ju is a scholar working on Molecular Biology, Computational Theory and Mathematics and Cancer Research. According to data from OpenAlex, Ying Ju has authored 33 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 5 papers in Cancer Research. Recurrent topics in Ying Ju's work include Machine Learning in Bioinformatics (21 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (8 papers). Ying Ju is often cited by papers focused on Machine Learning in Bioinformatics (21 papers), RNA and protein synthesis mechanisms (14 papers) and Genomics and Phylogenetic Studies (8 papers). Ying Ju collaborates with scholars based in China, Japan and Philippines. Ying Ju's co-authors include Quan Zou, Hua Tang, Dehui Yin, Yamei Luo, Ziyu Lin, Chenggang Song, Haoyu Zhang, Dong Chen, Xiangxiang Zeng and Meihong Wu and has published in prestigious journals such as Bioinformatics, PLoS ONE and Analytical Biochemistry.

In The Last Decade

Ying Ju

32 papers receiving 1.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Predicting Diabetes Mellitus With Machine Learning Techniques

2018 563 citations Quan Zou, Yamei Luo et al. Frontiers in Genetics profile →
Distance-based Support Vector Machine to Predict DNA N6-methyladenine Modification

2022 268 citations Quan Zou, Ying Ju et al. profile →

Peers

Countries citing papers authored by Ying Ju

Since Specialization

Citations

This map shows the geographic impact of Ying Ju's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ying Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Ju more than expected).

Fields of papers citing papers by Ying Ju

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ying Ju. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ying Ju. The network helps show where Ying Ju may publish in the future.

Co-authorship network of co-authors of Ying Ju

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Ju. A scholar is included among the top collaborators of Ying Ju based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ying Ju. Ying Ju is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	MiR-135a-5p regulates window of implantation by suppressing pinopodes development and decidualization of endometrial stromal cells 2024 ·Journal of Assisted Reproduction and Genetics ·(unknown), Ying Ju, (unknown), Jie Dong, (unknown), Jie Lu, Shuqiang Chen, Xiaohong Wang	5
2	STLBRF: an improved random forest algorithm based on standardized-threshold for feature screening of gene expression data 2024 ·Briefings in Functional Genomics ·(unknown), Ying Ju, Xiaofeng Yin, (unknown), Xu Zhang	1
3	Machine learning‐based antioxidant protein identification model: Progress and evaluation 2023 ·Journal of Cellular Biochemistry ·(unknown), Yue Pei, (unknown), Quan Zou, Ying Ju	1
4	Utilize a few features to classify presynaptic and postsynaptic neurotoxins 2022 ·Computers in Biology and Medicine ·(unknown), Qing Liu, Ying Ju	3
5	TMPpred: A support vector machine-based thermophilic protein identifier 2022 ·Analytical Biochemistry ·(unknown), Ying Ju, Hua Shi	12
6	iPseU-TWSVM: Identification of RNA pseudouridine sites based on TWSVM 2022 ·Mathematical Biosciences & Engineering ·(unknown), Xin Zhang, Ying Ju, Qing Liu, Yijie Ding	2
7	Application of Sparse Representation in Bioinformatics 2021 ·Frontiers in Genetics ·(unknown), (unknown), (unknown), Furong Tang, Lei Xu, Ying Ju, Lei Shi	7
8	CWLy-RF: A novel approach for identifying cell wall lyases based on random forest classifier 2021 ·Genomics ·(unknown), Lei Xu, Ying Ju	7
9	Research on the Computational Prediction of Essential Genes 2021 ·Frontiers in Cell and Developmental Biology ·(unknown), Ying Ju, Chen Dong, Lihong Wang	3
10	A Linear Regression Predictor for Identifying N6-Methyladenosine Sites Using Frequent Gapped K-mer Pattern 2019 ·Molecular Therapy — Nucleic Acids ·(unknown), (unknown), (unknown), Ying Ju, (unknown)	14
11	Predicting Diabetes Mellitus With Machine Learning Techniques breakdown → 2018 ·Frontiers in Genetics ·Quan Zou, (unknown), Yamei Luo, Dehui Yin, Ying Ju, Hua Tang	563
12	Sc-ncDNAPred: A Sequence-Based Predictor for Identifying Non-coding DNA in Saccharomyces cerevisiae 2018 ·Frontiers in Microbiology ·Wenying He, Ying Ju, Xiangxiang Zeng, Xiangrong Liu, Quan Zou	18
13	Prediction of G Protein-Coupled Receptors with SVM-Prot Features and Random Forest 2016 ·Scientifica ·Zhijun Liao, Ying Ju, Quan Zou	45
14	In SilicoPrediction of Gamma-Aminobutyric Acid Type-A Receptors Using Novel Machine-Learning-Based SVM and GBDT Approaches 2016 ·BioMed Research International ·Zhijun Liao, Yong Huang, Xiaodong Yue, Huijuan Lu, Ping Xuan, Ying Ju	32
15	Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology 2016 ·International Journal of Genomics ·(unknown), Ying Ju, Huijuan Lu, Ping Xuan, Quan Zou	25
16	Human Protein Subcellular Localization with Integrated Source and Multi-label Ensemble Classifier 2016 ·Scientific Reports ·Xiaotong Guo, Fulin Liu, Ying Ju, (unknown), Chunyu Wang	42
17	Resistance gene identification from Larimichthys crocea with machine learning techniques 2016 ·Scientific Reports ·(unknown), Zhijun Liao, Ying Ju, Juan Liu, Yong Mao, Xiangrong Liu	3
18	Pretata: predicting TATA binding proteins with novel features and dimensionality reduction strategy 2016 ·BMC Systems Biology ·Quan Zou, Shixiang Wan, Ying Ju, Jijun Tang, Xiangxiang Zeng	150
19	Complex Network Clustering by a Multi-objective Evolutionary Algorithm Based on Decomposition and Membrane Structure 2016 ·Scientific Reports ·Ying Ju, (unknown), (unknown), Xiangxiang Zeng, Xingyi Zhang	31
20	Finite Element Modeling and Simulating of Accommodating Human Crystalline Lens 2005 ·PubMed ·Zhuo Liu, Boliang Wang, (unknown), Ying Ju, (unknown), (unknown)	2

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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