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  1. A knowledge graph can effectively showcase the essential characteristics of data and is increasingly emerging as a significant means of integrating information in the field of artificial intelligence. Coronary...

    Authors: Jia-Ming Huan, Xiao-Jie Wang, Yuan Li, Shi-Jun Zhang, Yuan-Long Hu and Yun-Lun Li
    Citation: BioData Mining 2024 17:13
  2. Recent researches have found a strong correlation between the triglyceride-glucose (TyG) index or the atherogenic index of plasma (AIP) and cardiovascular disease (CVD) risk. However, there is a lack of resear...

    Authors: Yuqi Zhang, Sijin Li, Weijie Wu, Yanqing Zhao, Jintao Han, Chao Tong, Niansang Luo and Kun Zhang
    Citation: BioData Mining 2024 17:12
  3. Breast cancer is the most common malignancy among women worldwide. Despite advances in treating breast cancer over the past decades, drug resistance and adverse effects remain challenging. Recent therapeutic p...

    Authors: Thanyawee Srithanyarat, Kittisak Taoma, Thana Sutthibutpong, Marasri Ruengjitchatchawalya, Monrudee Liangruksa and Teeraphan Laomettachit
    Citation: BioData Mining 2024 17:8
  4. Epistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom fully explored as most approaches primarily focus on single-locus ...

    Authors: Sandra Batista, Vered Senderovich Madar, Philip J. Freda, Priyanka Bhandary, Attri Ghosh, Nicholas Matsumoto, Apurva S. Chitre, Abraham A. Palmer and Jason H. Moore
    Citation: BioData Mining 2024 17:7
  5. Previous studies have shown an association between gut microbiota and cardiovascular diseases (CVDs). However, the underlying causal relationship remains unclear. This study aims to elucidate the causal relati...

    Authors: Xiao-Ce Dai, Yi Yu, Si-Yu Zhou, Shuo Yu, Mei-Xiang Xiang and Hong Ma
    Citation: BioData Mining 2024 17:6
  6. Prioritizing candidate drugs based on genome-wide expression data is an emerging approach in systems pharmacology due to its holistic perspective for preclinical drug evaluation. In the current study, a networ...

    Authors: Regan Odongo, Asuman Demiroglu-Zergeroglu and Tunahan Çakır
    Citation: BioData Mining 2024 17:5
  7. Non-linear relationships at the genotype level are essential in understanding the genetic interactions of complex disease traits. Genome-wide association Studies (GWAS) have revealed statistical association of...

    Authors: Burcu Yaldız, Onur Erdoğan, Sevda Rafatov, Cem Iyigün and Yeşim Aydın Son
    Citation: BioData Mining 2024 17:3
  8. Nowadays, the chance of discovering the best antibody candidates for predicting clinical malaria has notably increased due to the availability of multi-sera data. The analysis of these data is typically divide...

    Authors: André Fonseca, Mikolaj Spytek, Przemysław Biecek, Clara Cordeiro and Nuno Sepúlveda
    Citation: BioData Mining 2024 17:2
  9. Although the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus (SLE) has required at least a positive anti-nuclear antibody (ANA) titer (≥ 1:80), it remains challenging for clinicians to ...

    Authors: Chih-Wei Chung, Seng-Cho Chou, Tzu-Hung Hsiao, Grace Joyce Zhang, Yu-Fang Chung and Yi-Ming Chen
    Citation: BioData Mining 2024 17:1
  10. The elderly are disproportionately affected by age-related hearing loss (ARHL). Despite being a well-known tool for ARHL evaluation, the Hearing Handicap Inventory for the Elderly Screening version (HHIE-S) ha...

    Authors: Tzong-Hann Yang, Yu-Fu Chen, Yen-Fu Cheng, Jue-Ni Huang, Chuan-Song Wu and Yuan-Chia Chu
    Citation: BioData Mining 2023 16:35
  11. Discrimination between patients affected by inflammatory bowel diseases and healthy controls on the basis of endoscopic imaging is an challenging problem for machine learning models. Such task is used here as ...

    Authors: Massimiliano Datres, Elisa Paolazzi, Marco Chierici, Matteo Pozzi, Antonio Colangelo, Marcello Dorian Donzella and Giuseppe Jurman
    Citation: BioData Mining 2023 16:33
  12. The governance of health systems is complex in nature due to several intertwined and multi-dimensional factors contributing to it. Recent challenges of health systems reflect the need for innovative approaches...

    Authors: Maryam Ramezani, Amirhossein Takian, Ahad Bakhtiari, Hamid R. Rabiee, Sadegh Ghazanfari and Saharnaz Sazgarnejad
    Citation: BioData Mining 2023 16:31
  13. Patients with Type 2 Diabetes Mellitus (T2DM) are at a higher risk of polypharmacy and more susceptible to irrational prescriptions; therefore, pharmacological therapy patterns are important to be monitored. T...

    Authors: Elnaz Ziad, Somayeh Sadat, Farshad Farzadfar and Mohammad-Reza Malekpour
    Citation: BioData Mining 2023 16:29
  14. Squiggle data is the numerical output of DNA and RNA sequencing by the Nanopore next generation sequencing platform. Nanopore sequencing offers expanded applications compared to previous sequencing techniques ...

    Authors: Naya Nagy, Matthew Stuart-Edwards, Marius Nagy, Liam Mitchell and Athanasios Zovoilis
    Citation: BioData Mining 2023 16:27
  15. Data-driven diabetes research has increased its interest in exploring the heterogeneity of the disease, aiming to support in the development of more specific prognoses and treatments within the so-called precisio...

    Authors: Nelson E. Ordoñez-Guillen, Jose Luis Gonzalez-Compean, Ivan Lopez-Arevalo, Miguel Contreras-Murillo and Edwin Aldana-Bobadilla
    Citation: BioData Mining 2023 16:24
  16. Deep learning models can infer cancer patient prognosis from molecular and anatomic pathology information. Recent studies that leveraged information from complementary multimodal data improved prognostication,...

    Authors: Zarif L. Azher, Anish Suvarna, Ji-Qing Chen, Ze Zhang, Brock C. Christensen, Lucas A. Salas, Louis J. Vaickus and Joshua J. Levy
    Citation: BioData Mining 2023 16:23
  17. The incidence of gastric cardiac cancer (GCC) has obviously increased recently with poor prognosis. It’s necessary to compare GCC prognosis with other gastric sites carcinoma and set up an effective prognostic...

    Authors: Wei Li, Minghang Zhang, Siyu Cai, Liangliang Wu, Chao Li, Yuqi He, Guibin Yang, Jinghui Wang and Yuanming Pan
    Citation: BioData Mining 2023 16:21
  18. The introduction of large language models (LLMs) that allow iterative “chat” in late 2022 is a paradigm shift that enables generation of text often indistinguishable from that written by humans. LLM-based chat...

    Authors: Jesse G. Meyer, Ryan J. Urbanowicz, Patrick C. N. Martin, Karen O’Connor, Ruowang Li, Pei-Chen Peng, Tiffani J. Bright, Nicholas Tatonetti, Kyoung Jae Won, Graciela Gonzalez-Hernandez and Jason H. Moore
    Citation: BioData Mining 2023 16:20
  19. Motor imagery brain-computer interfaces (BCIs) is a classic and potential BCI technology achieving brain computer integration. In motor imagery BCI, the operational frequency band of the EEG greatly affects th...

    Authors: Jing Luo, Jundong Li, Qi Mao, Zhenghao Shi, Haiqin Liu, Xiaoyong Ren and Xinhong Hei
    Citation: BioData Mining 2023 16:19
  20. Single-cell RNA-sequencing (scRNA-seq) data can serve as a good indicator of cell-to-cell heterogeneity and can aid in the study of cell growth by identifying cell types. Recently, advances in Variational Auto...

    Authors: Weiquan Pan, Faning Long and Jian Pan
    Citation: BioData Mining 2023 16:17
  21. In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) a...

    Authors: Tanapol Kosolwattana, Chenang Liu, Renjie Hu, Shizhong Han, Hua Chen and Ying Lin
    Citation: BioData Mining 2023 16:15
  22. Quantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort ...

    Authors: Philip J. Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S. Chitre, Oksana Polesskaya, Celine L. St. Pierre, Jianjun Gao, Connor D. Martin, Hao Chen, Angel G. Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli…
    Citation: BioData Mining 2023 16:14
  23. Clustering of genetic sequences is one of the key parts of bioinformatics analyses. Resulting phylogenetic trees are beneficial for solving many research questions, including tracing the history of species, st...

    Authors: Petr Ryšavý and Filip Železný
    Citation: BioData Mining 2023 16:13
  24. Automated data analysis and processing has the potential to assist, improve and guide decision making in medical practice. However, by now it has not yet been fully integrated in a clinical setting. Herein we ...

    Authors: Nico Schmid, Mihnea Ghinescu, Moritz Schanz, Micha Christ, Severin Schricker, Markus Ketteler, Mark Dominik Alscher, Ulrich Franke and Nora Goebel
    Citation: BioData Mining 2023 16:12
  25. Tuberculosis is a dangerous infectious disease with the largest number of reported cases in China every year. Preventing missed diagnosis has an important impact on the prevention, treatment, and recovery of t...

    Authors: Mengying Wang, Cuixia Lee, Zhenhao Wei, Hong Ji, Yingyun Yang and Cheng Yang
    Citation: BioData Mining 2023 16:11
  26. Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy b...

    Authors: Shuo-Ming Ou, Ming-Tsun Tsai, Kuo-Hua Lee, Wei-Cheng Tseng, Chih-Yu Yang, Tz-Heng Chen, Pin-Jie Bin, Tzeng-Ji Chen, Yao-Ping Lin, Wayne Huey-Herng Sheu, Yuan-Chia Chu and Der-Cherng Tarng
    Citation: BioData Mining 2023 16:8
  27. In recent years, convolutional neural networks (CNNs) have made great achievements in the field of medical image segmentation, especially full convolutional neural networks based on U-shaped structures and ski...

    Authors: Yun Jiang, Jinkun Dong, Tongtong Cheng, Yuan Zhang, Xin Lin and Jing Liang
    Citation: BioData Mining 2023 16:5
  28. Binary classification is a common task for which machine learning and computational statistics are used, and the area under the receiver operating characteristic curve (ROC AUC) has become the common standard ...

    Authors: Davide Chicco and Giuseppe Jurman
    Citation: BioData Mining 2023 16:4
  29. Loss-of-Function (LoF) variants in human genes are important due to their impact on clinical phenotypes and frequent occurrence in the genomes of healthy individuals. The association of LoF variants with compl...

    Authors: Abdulrahman Alasiri, Konrad J. Karczewski, Brian Cole, Bao-Li Loza, Jason H. Moore, Sander W. van der Laan, Folkert W. Asselbergs, Brendan J. Keating and Jessica van Setten
    Citation: BioData Mining 2023 16:3
  30. Anemia is one of the global public health problems that affect children and pregnant women. Anemia occurs when the level of red blood cells within the body decreases or when the structure of the red blood cell...

    Authors: Peter Appiahene, Justice Williams Asare, Emmanuel Timmy Donkoh, Giovanni Dimauro and Rosalia Maglietta
    Citation: BioData Mining 2023 16:2
  31. Urban parks constitute one of the main leisure areas, especially for the most vulnerable people in our society, children, and the elderly. Contact with soils can pose a health risk. Microbiological testing is ...

    Authors: Diego Arnal, Celeste Moya, Luigi Filippelli, Jaume Segura-Garcia and Sergi Maicas
    Citation: BioData Mining 2023 16:1

Annual Journal Metrics

  • 2022 Citation Impact
    4.5 - 2-year Impact Factor
    4.4 - 5-year Impact Factor
    1.022 - SNIP (Source Normalized Impact per Paper)
    0.913 - SJR (SCImago Journal Rank)

    2023 Speed
    32 days submission to first editorial decision for all manuscripts (Median)
    171 days submission to accept (Median)

    2023 Usage 
    146 Altmetric mentions