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Machine Learning and Artificial Intelligence in Bioinformatics

Section edited by Jean-Philippe Vert

This section covers recent advances in machine learning and artificial intelligence methods, including their applications to problems in bioinformatics. It considers manuscripts describing novel computational techniques to analyse high throughput data such as sequences and gene/protein expressions, as well as machine learning techniques such as graphical models, neural networks or kernel methods.

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  1. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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

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  10. 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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  11. 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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  12. 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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  13. 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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  14. Late-Onset Alzheimer’s Disease (LOAD) is a leading form of dementia. There is no effective cure for LOAD, leaving the treatment efforts to depend on preventive cognitive therapies, which stand to benefit from ...

    Authors: Javier De Velasco Oriol, Edgar E. Vallejo, Karol Estrada, José Gerardo Taméz Peña and The Alzheimer’s Disease Neuroimaging Initiative

    Citation: BMC Bioinformatics 2019 20:709

    Content type: Research Article

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  15. Next generation sequencing instruments are providing new opportunities for comprehensive analyses of cancer genomes. The increasing availability of tumor data allows to research the complexity of cancer diseas...

    Authors: Martin Palazzo, Pierre Beauseroy and Patricio Yankilevich

    Citation: BMC Bioinformatics 2019 20:655

    Content type: Methodology Article

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  16. 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

  17. 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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  18. 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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  19. Recurrent neural network(RNN) is a good way to process sequential data, but the capability of RNN to compute long sequence data is inefficient. As a variant of RNN, long short term memory(LSTM) solved the prob...

    Authors: Jiale Liu and Xinqi Gong

    Citation: BMC Bioinformatics 2019 20:609

    Content type: Methodology Article

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  20. 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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  21. 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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  22. 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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  23. 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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  24. 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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  25. 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

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  26. When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient’s phenotypes. Typically, this is done through annotation, fil...

    Authors: James M. Holt, Brandon Wilk, Camille L. Birch, Donna M. Brown, Manavalan Gajapathy, Alexander C. Moss, Nadiya Sosonkina, Melissa A. Wilk, Julie A. Anderson, Jeremy M. Harris, Jacob M. Kelly, Fariba Shaterferdosian, Angelina E. Uno-Antonison, Arthur Weborg and Elizabeth A. Worthey

    Citation: BMC Bioinformatics 2019 20:496

    Content type: Research Article

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  27. The analysis of health and medical data is crucial for improving the diagnosis precision, treatments and prevention. In this field, machine learning techniques play a key role. However, the amount of health da...

    Authors: Josefa Díaz Álvarez, Jordi A. Matias-Guiu, María Nieves Cabrera-Martín, José L. Risco-Martín and José L. Ayala

    Citation: BMC Bioinformatics 2019 20:491

    Content type: Methodology Article

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  28. The data deluge can leverage sophisticated ML techniques for functionally annotating the regulatory non-coding genome. The challenge lies in selecting the appropriate classifier for the specific functional ann...

    Authors: Chih-Hao Fang, Nawanol Theera-Ampornpunt, Michael A. Roth, Ananth Grama and Somali Chaterji

    Citation: BMC Bioinformatics 2019 20:488

    Content type: Research Article

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  29. MicroRNAs (miRNAs) are noncoding RNA molecules heavily involved in human tumors, in which few of them circulating the human body. Finding a tumor-associated signature of miRNA, that is, the minimum miRNA entit...

    Authors: Alejandro Lopez-Rincon, Marlet Martinez-Archundia, Gustavo U. Martinez-Ruiz, Alexander Schoenhuth and Alberto Tonda

    Citation: BMC Bioinformatics 2019 20:480

    Content type: Research Article

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  30. The adverse reactions that are caused by drugs are potentially life-threatening problems. Comprehensive knowledge of adverse drug reactions (ADRs) can reduce their detrimental impacts on patients. Detecting AD...

    Authors: Tongxuan Zhang, Hongfei Lin, Yuqi Ren, Liang Yang, Bo Xu, Zhihao Yang, Jian Wang and Yijia Zhang

    Citation: BMC Bioinformatics 2019 20:479

    Content type: Research Article

    Published on:

  31. Binding sites are the pockets of proteins that can bind drugs; the discovery of these pockets is a critical step in drug design. With the help of computers, protein pockets prediction can save manpower and fin...

    Authors: Mingjian Jiang, Zhen Li, Yujie Bian and Zhiqiang Wei

    Citation: BMC Bioinformatics 2019 20:478

    Content type: Methodology Article

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2019 Journal Metrics

  • Citation Impact
    3.242 - 2-year Impact Factor
    3.213 - 5-year Impact Factor
    1.156 - Source Normalized Impact per Paper (SNIP)
    1.626 - SCImago Journal Rank (SJR)

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