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Machine Learning and Artificial Intelligence in Bioinformatics

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  1. Inferring diseases related to the patient’s electronic medical records (EMRs) is of great significance for assisting doctor diagnosis. Several recent prediction methods have shown that deep learning-based meth...

    Authors: Tong Wang, Ping Xuan, Zonglin Liu and Tiangang Zhang

    Citation: BMC Bioinformatics 2020 21:230

    Content type: Methodology article

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  3. The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accura...

    Authors: Ali Haisam Muhammad Rafid, Md. Toufikuzzaman, Mohammad Saifur Rahman and M. Sohel Rahman

    Citation: BMC Bioinformatics 2020 21:223

    Content type: Methodology Article

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  4. Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these databases struggle to keep up with the exponential growth of th...

    Authors: Emily K. Mallory, Matthieu de Rochemonteix, Alex Ratner, Ambika Acharya, Chris Re, Roselie A. Bright and Russ B. Altman

    Citation: BMC Bioinformatics 2020 21:217

    Content type: Research article

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  5. Semantic resources such as knowledge bases contains high-quality-structured knowledge and therefore require significant effort from domain experts. Using the resources to reinforce the information retrieval fr...

    Authors: Zhijing Li, Yuchen Lian, Xiaoyong Ma, Xiangrong Zhang and Chen Li

    Citation: BMC Bioinformatics 2020 21:213

    Content type: Methodology article

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  6. Apoptosis, also called programmed cell death, refers to the spontaneous and orderly death of cells controlled by genes in order to maintain a stable internal environment. Identifying the subcellular location o...

    Authors: Lei Du, Qingfang Meng, Yuehui Chen and Peng Wu

    Citation: BMC Bioinformatics 2020 21:212

    Content type: Methodology Article

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  7. The aim of gene expression-based clinical modelling in tumorigenesis is not only to accurately predict the clinical endpoints, but also to reveal the genome characteristics for downstream analysis for the purp...

    Authors: Yiru Zhao, Yifan Zhou, Yuan Liu, Yinyi Hao, Menglong Li, Xuemei Pu, Chuan Li and Zhining Wen

    Citation: BMC Bioinformatics 2020 21:195

    Content type: Methodology article

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  8. The necessity to analyze medium-throughput data in epidemiological studies with small sample size, particularly when studying biomedical data may hinder the use of classical statistical methods. Support vector...

    Authors: Hector Sanz, Ferran Reverter and Clarissa Valim

    Citation: BMC Bioinformatics 2020 21:193

    Content type: Methodology article

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    The Correction to this article has been published in BMC Bioinformatics 2020 21:371

  9. In addition to causing the pandemic influenza outbreaks of 1918 and 2009, subtype H1N1 influenza A viruses (IAVs) have caused seasonal epidemics since 1977. Antigenic property of influenza viruses are determin...

    Authors: Lei Li, Deborah Chang, Lei Han, Xiaojian Zhang, Joseph Zaia and Xiu-Feng Wan

    Citation: BMC Bioinformatics 2020 21:182

    Content type: Methodology article

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  10. Recently, DNA methylation has drawn great attention due to its strong correlation with abnormal gene activities and informative representation of the cancer status. As a number of studies focus on DNA methylat...

    Authors: Joungmin Choi and Heejoon Chae

    Citation: BMC Bioinformatics 2020 21:181

    Content type: Research Article

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  13. While clinical trials are considered the gold standard for detecting adverse events, often these trials are not sufficiently powered to detect difficult to observe adverse events. We developed a preliminary ap...

    Authors: Chathuri Daluwatte, Peter Schotland, David G. Strauss, Keith K. Burkhart and Rebecca Racz

    Citation: BMC Bioinformatics 2020 21:163

    Content type: Research article

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  16. Recent years have witnessed an increasing interest in multi-omics data, because these data allow for better understanding complex diseases such as cancer on a molecular system level. In addition, multi-omics d...

    Authors: Amina Lemsara, Salima Ouadfel and Holger Fröhlich

    Citation: BMC Bioinformatics 2020 21:146

    Content type: Methodology article

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  17. Feature selection in class-imbalance learning has gained increasing attention in recent years due to the massive growth of high-dimensional class-imbalanced data across many scientific fields. In addition to r...

    Authors: Guang-Hui Fu, Yuan-Jiao Wu, Min-Jie Zong and Jianxin Pan

    Citation: BMC Bioinformatics 2020 21:121

    Content type: Research Article

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  18. The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatu...

    Authors: Aaron M. Smith, Jonathan R. Walsh, John Long, Craig B. Davis, Peter Henstock, Martin R. Hodge, Mateusz Maciejewski, Xinmeng Jasmine Mu, Stephen Ra, Shanrong Zhao, Daniel Ziemek and Charles K. Fisher

    Citation: BMC Bioinformatics 2020 21:119

    Content type: Research Article

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  21. MicroRNA (miRNA) regulation is associated with several diseases, including neurodegenerative diseases. Several approaches can be used for modeling miRNA regulation. However, their precision may be limited for ...

    Authors: Lucile Mégret, Satish Sasidharan Nair, Julia Dancourt, Jeff Aaronson, Jim Rosinski and Christian Neri

    Citation: BMC Bioinformatics 2020 21:75

    Content type: Research article

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  22. The study of functional associations between ncRNAs and human diseases is a pivotal task of modern research to develop new and more effective therapeutic approaches. Nevertheless, it is not a trivial task sinc...

    Authors: Emanuele Pio Barracchia, Gianvito Pio, Domenica D’Elia and Michelangelo Ceci

    Citation: BMC Bioinformatics 2020 21:70

    Content type: Methodology Article

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  23. Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between gene...

    Authors: Yu-Chuan Chang, June-Tai Wu, Ming-Yi Hong, Yi-An Tung, Ping-Han Hsieh, Sook Wah Yee, Kathleen M. Giacomini, Yen-Jen Oyang and Chien-Yu Chen

    Citation: BMC Bioinformatics 2020 21:68

    Content type: Software

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  24. Single-cell RNA sequencing (scRNA-seq) is an emerging technology that can assess the function of an individual cell and cell-to-cell variability at the single cell level in an unbiased manner. Dimensionality r...

    Authors: Eugene Lin, Sudipto Mukherjee and Sreeram Kannan

    Citation: BMC Bioinformatics 2020 21:64

    Content type: Methodology article

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  26. Feature selection is a crucial step in machine learning analysis. Currently, many feature selection approaches do not ensure satisfying results, in terms of accuracy and computational time, when the amount of ...

    Authors: Mattia Chiesa, Giada Maioli, Gualtiero I. Colombo and Luca Piacentini

    Citation: BMC Bioinformatics 2020 21:54

    Content type: Software

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  31. Various methods for differential expression analysis have been widely used to identify features which best distinguish between different categories of samples. Multiple hypothesis testing may leave out explana...

    Authors: Xudong Zhao, Qing Jiao, Hangyu Li, Yiming Wu, Hanxu Wang, Shan Huang and Guohua Wang

    Citation: BMC Bioinformatics 2020 21:43

    Content type: Software

    Published on:

  32. Automated biomedical named entity recognition and normalization serves as the basis for many downstream applications in information management. However, this task is challenging due to name variations and enti...

    Authors: Huiwei Zhou, Shixian Ning, Zhe Liu, Chengkun Lang, Zhuang Liu and Bizun Lei

    Citation: BMC Bioinformatics 2020 21:35

    Content type: Research article

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  33. MicroRNAs (miRNAs) play important roles in a variety of biological processes by regulating gene expression at the post-transcriptional level. So, the discovery of new miRNAs has become a popular task in biolog...

    Authors: Xueming Zheng, Xingli Fu, Kaicheng Wang and Meng Wang

    Citation: BMC Bioinformatics 2020 21:17

    Content type: Methodology article

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  36. With the global spread of multidrug resistance in pathogenic microbes, infectious diseases emerge as a key public health concern of the recent time. Identification of host genes associated with infectious dise...

    Authors: Ranjan Kumar Barman, Anirban Mukhopadhyay, Ujjwal Maulik and Santasabuj Das

    Citation: BMC Bioinformatics 2019 20:736

    Content type: Research article

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  38. Predicting protein function and structure from sequence is one important challenge for computational biology. For 26 years, most state-of-the-art approaches combined machine learning and evolutionary informati...

    Authors: Michael Heinzinger, Ahmed Elnaggar, Yu Wang, Christian Dallago, Dmitrii Nechaev, Florian Matthes and Burkhard Rost

    Citation: BMC Bioinformatics 2019 20:723

    Content type: Research article

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  39. In short-read DNA sequencing experiments, the read coverage is a key parameter to successfully assemble the reads and reconstruct the sequence of the input DNA. When coverage is very low, the original sequence...

    Authors: Louis Ranjard, Thomas K. F. Wong and Allen G. Rodrigo

    Citation: BMC Bioinformatics 2019 20:654

    Content type: Research Article

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    The Correction to this article has been published in BMC Bioinformatics 2020 21:24

  40. Computational compound repositioning has the potential for identifying new uses for existing drugs, and new algorithms and data source aggregation strategies provide ever-improving results via in silico metric...

    Authors: Michael Mayers, Tong Shu Li, Núria Queralt-Rosinach and Andrew I. Su

    Citation: BMC Bioinformatics 2019 20:653

    Content type: Research article

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  41. The Bacteria Biotope (BB) task is a biomedical relation extraction (RE) that aims to study the interaction between bacteria and their locations. This task is considered to pertain to fundamental knowledge in a...

    Authors: Amarin Jettakul, Duangdao Wichadakul and Peerapon Vateekul

    Citation: BMC Bioinformatics 2019 20:627

    Content type: Research Article

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  42. Microarray datasets consist of complex and high-dimensional samples and genes, and generally the number of samples is much smaller than the number of genes. Due to this data imbalance, gene selection is a dema...

    Authors: Russul Alanni, Jingyu Hou, Hasseeb Azzawi and Yong Xiang

    Citation: BMC Bioinformatics 2019 20:608

    Content type: Research article

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  43. De novo drug discovery is a time-consuming and expensive process. Nowadays, drug repositioning is utilized as a common strategy to discover a new drug indication for existing drugs. This strategy is mostly use...

    Authors: Mahroo Moridi, Marzieh Ghadirinia, Ali Sharifi-Zarchi and Fatemeh Zare-Mirakabad

    Citation: BMC Bioinformatics 2019 20:577

    Content type: Research article

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  46. Cancer subtype classification attains the great importance for accurate diagnosis and personalized treatment of cancer. Latest developments in high-throughput sequencing technologies have rapidly produced mult...

    Authors: Jing Xu, Peng Wu, Yuehui Chen, Qingfang Meng, Hussain Dawood and Hassan Dawood

    Citation: BMC Bioinformatics 2019 20:527

    Content type: Methodology Article

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  47. Network inference is crucial for biomedicine and systems biology. Biological entities and their associations are often modeled as interaction networks. Examples include drug protein interaction or gene regulat...

    Authors: Konstantinos Pliakos and Celine Vens

    Citation: BMC Bioinformatics 2019 20:525

    Content type: Research Article

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  48. Protein subcellular localization plays a crucial role in understanding cell function. Proteins need to be in the right place at the right time, and combine with the corresponding molecules to fulfill their fun...

    Authors: Fan Yang, Yang Liu, Yanbin Wang, Zhijian Yin and Zhen Yang

    Citation: BMC Bioinformatics 2019 20:522

    Content type: Research article

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  49. Quantitative structure-activity relationship (QSAR) is a computational modeling method for revealing relationships between structural properties of chemical compounds and biological activities. QSAR modeling i...

    Authors: Sunyoung Kwon, Ho Bae, Jeonghee Jo and Sungroh Yoon

    Citation: BMC Bioinformatics 2019 20:521

    Content type: Methodology Article

    Published on: