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  1. 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
    Content type: Methodology Published on:

  2. 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
    Content type: Research Published on:

  4. 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
    Content type: Research Published on:

  6. 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
    Content type: Research Published on:

  7. 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
    Content type: Research Published on:

  9. 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
    Content type: Research Published on:

  10. Gene set enrichment analysis (GSEA) uses gene-level univariate associations to identify gene set-phenotype associations for hypothesis generation and interpretation. We propose that GSEA can be adapted to inco...

    Authors: Alexa A. Woodward, Deanne M. Taylor, Elizabeth Goldmuntz, Laura E. Mitchell, A.J. Agopian, Jason H. Moore and Ryan J. Urbanowicz
    Citation: BioData Mining 2022 15:4
    Content type: Methodology Published on:

  11. Lysine succinylation is a type of protein post-translational modification which is widely involved in cell differentiation, cell metabolism and other important physiological activities. To study the molecular ...

    Authors: Ying Zeng, Yuan Chen and Zheming Yuan
    Citation: BioData Mining 2022 15:3
    Content type: Research Published on:

  12. The mTOR-PI3K-Akt pathway influences cell metabolism and (malignant) cell growth. We generated sex-specific polygenic risk scores capturing natural variation in 7 out of 10 top-ranked genes in this pathway. We...

    Authors: Colinda C.J.M. Simons, Leo J. Schouten, Roger W.L. Godschalk, Frederik-Jan van Schooten, Monika Stoll, Kristel Van Steen, Piet A. van den Brandt and Matty P. Weijenberg
    Citation: BioData Mining 2022 15:2
    Content type: Research Published on:

  13. Single-cell RNA sequencing (scRNA-seq) data provide valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applicatio...

    Authors: Pelin Gundogdu, Carlos Loucera, Inmaculada Alamo-Alvarez, Joaquin Dopazo and Isabel Nepomuceno
    Citation: BioData Mining 2022 15:1
    Content type: Methodology Published on:

  14. Rheumatoid arthritis (RA) and systemic lupus erythematous (SLE) are autoimmune rheumatic diseases that share a complex genetic background and common clinical features. This study’s purpose was to construct mac...

    Authors: Chih-Wei Chung, Tzu-Hung Hsiao, Chih-Jen Huang, Yen-Ju Chen, Hsin-Hua Chen, Ching-Heng Lin, Seng-Cho Chou, Tzer-Shyong Chen, Yu-Fang Chung, Hwai-I Yang and Yi-Ming Chen
    Citation: BioData Mining 2021 14:52
    Content type: Research Published on:

  15. With the increase in the size of genomic datasets describing variability in populations, extracting relevant information becomes increasingly useful as well as complex. Recently, computational methodologies su...

    Authors: Arnaud Nguembang Fadja, Fabrizio Riguzzi, Giorgio Bertorelle and Emiliano Trucchi
    Citation: BioData Mining 2021 14:51
    Content type: Research Published on:

  16. Long noncoding RNAs (lncRNAs) have dense linkages with various biological processes. Identifying interacting lncRNA-protein pairs contributes to understand the functions and mechanisms of lncRNAs. Wet experime...

    Authors: Lihong Peng, Ruya Yuan, Ling Shen, Pengfei Gao and Liqian Zhou
    Citation: BioData Mining 2021 14:50
    Content type: Research Published on:

  22. Missing data is a common issue in different fields, such as electronics, image processing, medical records and genomics. They can limit or even bias the posterior analysis. The data collection process can lead...

    Authors: Ben Omega Petrazzini, Hugo Naya, Fernando Lopez-Bello, Gustavo Vazquez and Lucía Spangenberg
    Citation: BioData Mining 2021 14:44
    Content type: Research Published on:

  23. The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of...

    Authors: Inese Polaka, Danute Razuka-Ebela, Jin Young Park and Marcis Leja
    Citation: BioData Mining 2021 14:43
    Content type: Research Published on:

  24. Glioblastoma (GBM) is the most aggressive and prevalent primary brain tumor, with a median survival of 15 months. Advancements in multi-omics profiling combined with computational algorithms have unraveled the...

    Authors: Miquel Ensenyat-Mendez, Sandra Íñiguez-Muñoz, Borja Sesé and Diego M. Marzese
    Citation: BioData Mining 2021 14:42
    Content type: Research Published on:

    The Correction to this article has been published in BioData Mining 2021 14:47

  26. Early prediction of hospital mortality is crucial for ICU patients with sepsis. This study aimed to develop a novel blending machine learning (ML) model for hospital mortality prediction in ICU patients with s...

    Authors: Zhixuan Zeng, Shuo Yao, Jianfei Zheng and Xun Gong
    Citation: BioData Mining 2021 14:40
    Content type: Research Published on:

  28. Although many patients receive good prognoses with standard therapy, 30–50% of diffuse large B-cell lymphoma (DLBCL) cases may relapse after treatment. Statistical or computational intelligent models are power...

    Authors: Shuanglong Fan, Zhiqiang Zhao, Yanbo Zhang, Hongmei Yu, Chuchu Zheng, Xueqian Huang, Zhenhuan Yang, Meng Xing, Qing Lu and Yanhong Luo
    Citation: BioData Mining 2021 14:38
    Content type: Research Published on:

  29. The last decade has seen a major increase in the availability of genomic data. This includes expert-curated databases that describe the biological activity of genes, as well as high-throughput assays that meas...

    Authors: Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta and Svetha Venkatesh
    Citation: BioData Mining 2021 14:37
    Content type: Research Published on:

  30. GenoVault is a cloud-based repository for handling Next Generation Sequencing (NGS) data. It is developed using OpenStack-based private cloud with various services like keystone for authentication, cinder for ...

    Authors: Sankalp Jain, Amit Saxena, Suprit Hesarur, Kirti Bhadhadhara, Neeraj Bharti, Sunitha Manjari Kasibhatla, Uddhavesh Sonavane and Rajendra Joshi
    Citation: BioData Mining 2021 14:36
    Content type: Software article Published on:

  31. Calcific aortic valve stenosis (CAVS) is a fatal disease and there is no pharmacological treatment to prevent the progression of CAVS. This study aims to identify genes potentially implicated with CAVS in pati...

    Authors: Erika Cantor, Rodrigo Salas, Harvey Rosas and Sandra Guauque-Olarte
    Citation: BioData Mining 2021 14:35
    Content type: Research Published on:

  33. Chronic Obstructive Pulmonary Disease (COPD) is one of the top 10 causes of death worldwide, representing a major public health problem. Researchers have been looking for new technologies and methods for patie...

    Authors: Juliana Alves Pegoraro, Sophie Lavault, Nicolas Wattiez, Thomas Similowski, Jésus Gonzalez-Bermejo and Etienne Birmelé
    Citation: BioData Mining 2021 14:33
    Content type: Research Published on:

  34. Genomic studies increasingly integrate expression quantitative trait loci (eQTL) information into their analysis pipelines, but few tools exist for the visualization of colocalization between eQTL and GWAS res...

    Authors: Theodore G. Drivas, Anastasia Lucas and Marylyn D. Ritchie
    Citation: BioData Mining 2021 14:32
    Content type: Software article Published on:

  35. High-throughput sequencing enables the analysis of the composition of numerous biological systems, such as microbial communities. The identification of dependencies within these systems requires the analysis a...

    Authors: Sebastian Racedo, Ivan Portnoy, Jorge I. Vélez, Homero San-Juan-Vergara, Marco Sanjuan and Eduardo Zurek
    Citation: BioData Mining 2021 14:31
    Content type: Methodology Published on:

  37. Hepatocellular carcinoma (HCC) is a disease with a high incidence and a poor prognosis. Growing amounts of evidence have shown that the immune system plays a critical role in the biological processes of HCC su...

    Authors: Qian Yan, Wenjiang Zheng, Boqing Wang, Baoqian Ye, Huiyan Luo, Xinqian Yang, Ping Zhang and Xiongwen Wang
    Citation: BioData Mining 2021 14:29
    Content type: Research Published on:

    The Correction to this article has been published in BioData Mining 2023 16:30

  38. Machine learning approaches for predicting disease risk from high-dimensional whole genome sequence (WGS) data often result in unstable models that can be difficult to interpret, limiting the identification of...

    Authors: Maya Varma, Kelley M. Paskov, Brianna S. Chrisman, Min Woo Sun, Jae-Yoon Jung, Nate T. Stockham, Peter Y. Washington and Dennis P. Wall
    Citation: BioData Mining 2021 14:28
    Content type: Research Published on:

  39. As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-ca...

    Authors: Kelley Paskov, Jae-Yoon Jung, Brianna Chrisman, Nate T. Stockham, Peter Washington, Maya Varma, Min Woo Sun and Dennis P. Wall
    Citation: BioData Mining 2021 14:27
    Content type: Research Published on:

  40. As per the 2017 WHO fact sheet, Coronary Artery Disease (CAD) is the primary cause of death in the world, and accounts for 31% of total fatalities. The unprecedented 17.6 million deaths caused by CAD in 2016 u...

    Authors: Seema Singh Saharan, Pankaj Nagar, Kate Townsend Creasy, Eveline O. Stock, James Feng, Mary J. Malloy and John P. Kane
    Citation: BioData Mining 2021 14:26
    Content type: Research Published on:

  41. Longitudinal gene expression analysis and survival modeling have been proved to add valuable biological and clinical knowledge. This study proposes a novel framework to discover gene signatures and patterns in...

    Authors: Cláudia S. Constantino, Alexandra M. Carvalho and Susana Vinga
    Citation: BioData Mining 2021 14:25
    Content type: Methodology Published on:

  42. Aortic dissection (AD) is one of the most catastrophic aortic diseases associated with a high mortality rate. In contrast to the advances in most cardiovascular diseases, both the incidence and in-hospital mor...

    Authors: Peng Qiu, Yixuan Li, Kai Liu, Jinbao Qin, Kaichuang Ye, Tao Chen and Xinwu Lu
    Citation: BioData Mining 2021 14:24
    Content type: Research Published on:

  43. Acute heart failure (AHF) is associated with significant morbidity and mortality. Effective patient risk stratification is essential to guiding hospitalization decisions and the clinical management of AHF. Cli...

    Authors: Ashwath Radhachandran, Anurag Garikipati, Nicole S. Zelin, Emily Pellegrini, Sina Ghandian, Jacob Calvert, Jana Hoffman, Qingqing Mao and Ritankar Das
    Citation: BioData Mining 2021 14:23
    Content type: Research Published on:

  46. The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019. However, analysis has focused primarily on single nucleotide polymorphisms and largely ...

    Authors: Brianna Sierra Chrisman, Kelley Paskov, Nate. Stockham, Kevin Tabatabaei, Jae-Yoon Jung, Peter Washington, Maya Varma, Min Woo Sun, Sepideh Maleki and Dennis P. Wall
    Citation: BioData Mining 2021 14:20
    Content type: Research Published on:

  49. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely employed to reduce multi-levels of gene-gene interactions into high- or low-risk groups using a binary ...

    Authors: Jung Wun Lee and Seungyeoun Lee
    Citation: BioData Mining 2021 14:17
    Content type: Methodology Published on:

  50. In genome-wide association studies the extent and impact of confounding due to population structure have been well recognized. Inadequate handling of such confounding is likely to lead to spurious associations...

    Authors: Fentaw Abegaz, François Van Lishout, Jestinah M. Mahachie John, Kridsadakorn Chiachoompu, Archana Bhardwaj, Diane Duroux, Elena S. Gusareva, Zhi Wei, Hakon Hakonarson and Kristel Van Steen
    Citation: BioData Mining 2021 14:16
    Content type: Methodology Published on:
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BioData Mining

ISSN: 1756-0381