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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. Cancer is one of the leading causes of death worldwide and can be caused by environmental aspects (for example, exposure to asbestos), by human behavior (such as smoking), or by genetic factors. To understand ...

    Authors: Davide Chicco, Abbas Alameer, Sara Rahmati and Giuseppe Jurman
    Citation: BioData Mining 2022 15:28
  18. Knowledge graphs support biomedical research efforts by providing contextual information for biomedical entities, constructing networks, and supporting the interpretation of high-throughput analyses. These dat...

    Authors: David N. Nicholson, Daniel S. Himmelstein and Casey S. Greene
    Citation: BioData Mining 2022 15:26
  19. The expanding body of potential therapeutic targets requires easily accessible, structured, and transparent real-time interpretation of molecular data. Open-access genomic, proteomic and drug-repurposing datab...

    Authors: David Dora, Timea Dora, Gabor Szegvari, Csongor Gerdán and Zoltan Lohinai
    Citation: BioData Mining 2022 15:25
  20. Machine learning can be used to predict the different onset of human cancers. Highly dimensional data have enormous, complicated problems. One of these is an excessive number of genes plus over-fitting, fittin...

    Authors: Noura Mohammed Abdelwahed, Gh. S. El-Tawel and M. A. Makhlouf
    Citation: BioData Mining 2022 15:24
  21. Clinical decision of extubation is a challenge in the treatment of patient with invasive mechanical ventilation (IMV), since existing extubation protocols are not capable of precisely predicting extubation fai...

    Authors: Zhixuan Zeng, Xianming Tang, Yang Liu, Zhengkun He and Xun Gong
    Citation: BioData Mining 2022 15:21
  22. Under-five mortality is a matter of serious concern for child health as well as the social development of any country. The paper aimed to find the accuracy of machine learning models in predicting under-five m...

    Authors: Rakesh Kumar Saroj, Pawan Kumar Yadav, Rajneesh Singh and Obvious.N. Chilyabanyama
    Citation: BioData Mining 2022 15:20
  23. The three-dimensional (3D) structure of chromatin has a massive effect on its function. Because of this, it is desirable to have an understanding of the 3D structural organization of chromatin. To gain greater...

    Authors: David Vadnais, Michael Middleton and Oluwatosin Oluwadare
    Citation: BioData Mining 2022 15:19
  24. Nowadays, patients with chronic diseases such as diabetes and hypertension have reached alarming numbers worldwide. These diseases increase the risk of developing acute complications and involve a substantial ...

    Authors: David Chushig-Muzo, Cristina Soguero-Ruiz, Pablo de Miguel Bohoyo and Inmaculada Mora-Jiménez
    Citation: BioData Mining 2022 15:18
  25. Preterm deliveries have many negative health implications on both mother and child. Identifying the population level factors that increase the risk of preterm deliveries is an important step in the direction o...

    Authors: Zeineb Safi, Neethu Venugopal, Haytham Ali, Michel Makhlouf, Faisal Farooq and Sabri Boughorbel
    Citation: BioData Mining 2022 15:17
  26. Cardiopulmonary exercise testing (CPET) provides a reliable and reproducible approach to measuring fitness in patients and diagnosing their health problems. However, the data from CPET consist of multiple time...

    Authors: Donald E. Brown, Suchetha Sharma, James A. Jablonski and Arthur Weltman
    Citation: BioData Mining 2022 15:16
  27. Single-cell RNA-seq overcomes the shortcomings of conventional transcriptome sequencing technology and could provide a powerful tool for distinguishing the transcriptome characteristics of various cell types i...

    Authors: Bin Yang, Wenzheng Bao, Baitong Chen and Dan Song
    Citation: BioData Mining 2022 15:13
  28. Cancer molecular subtyping plays a critical role in individualized patient treatment. In previous studies, high-throughput gene expression signature-based methods have been proposed to identify cancer subtypes...

    Authors: Shaochuan Li, Yuning Yang, Xin Wang, Jun Li, Jun Yu, Xiangtao Li and Ka-Chun Wong
    Citation: BioData Mining 2022 15:12
  29. Thanks to the wider spread of high-throughput experimental techniques, biologists are accumulating large amounts of datasets which often mix quantitative and qualitative variables and are not always complete, ...

    Authors: Rayan Eid, Claudine Landès, Alix Pernet, Emmanuel Benoît, Pierre Santagostini, Angelina El Ghaziri and Julie Bourbeillon
    Citation: BioData Mining 2022 15:10
  30. This work presents mSRFR (microalgae SMOTE Random Forest Relief model), a classification tool for noncoding RNAs (ncRNAs) in microalgae, including green algae, diatoms, golden algae, and cyanobacteria. First, ...

    Authors: Songtham Anuntakarun, Supatcha Lertampaiporn, Teeraphan Laomettachit, Warin Wattanapornprom and Marasri Ruengjitchatchawalya
    Citation: BioData Mining 2022 15:8
  31. The advent of high-throughput transcriptomic screening technologies has resulted in a wealth of publicly available gene expression data associated with chemical treatments. From a regulatory perspective, data ...

    Authors: Joseph L. Bundy, Richard Judson, Antony J. Williams, Chris Grulke, Imran Shah and Logan J. Everett
    Citation: BioData Mining 2022 15:7
  32. Symptom-based machine learning models for disease detection are a way to reduce the workload of doctors when they have too many patients. Currently, there are many research studies on machine learning or deep ...

    Authors: Wanchaloem Nadda, Waraporn Boonchieng and Ekkarat Boonchieng
    Citation: BioData Mining 2022 15:5

Annual Journal Metrics

  • Citation Impact 2023
    Journal Impact Factor: 4.0
    5-year Journal Impact Factor: 3.7
    Source Normalized Impact per Paper (SNIP): 1.413
    SCImago Journal Rank (SJR): 0.958

    Speed 2023
    Submission to first editorial decision (median days): 15
    Submission to acceptance (median days): 171

    Usage 2023
    Downloads: 400,374
    Altmetric mentions: 146