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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. 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

    Published on:

  2. 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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  3. 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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  4. 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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  5. 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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  6. 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

  7. 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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  8. 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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  9. 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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  10. 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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  11. 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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  12. 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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  13. 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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  14. 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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  15. 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:

  16. 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

    Published on:

  17. 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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  18. 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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  19. 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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  20. 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:

  21. 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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  22. Long-chain non-coding RNA (lncRNA) is closely related to many biological activities. Since its sequence structure is similar to that of messenger RNA (mRNA), it is difficult to distinguish between the two base...

    Authors: Jianghui Wen, Yeshu Liu, Yu Shi, Haoran Huang, Bing Deng and Xinping Xiao

    Citation: BMC Bioinformatics 2019 20:469

    Content type: Methodology article

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  23. MiRNAs play significant roles in many fundamental and important biological processes, and predicting potential miRNA-disease associations makes contributions to understanding the molecular mechanism of human d...

    Authors: Yuchong Gong, Yanqing Niu, Wen Zhang and Xiaohong Li

    Citation: BMC Bioinformatics 2019 20:468

    Content type: Research article

    Published on:

  24. Although many of the genic features in Mycobacterium abscessus have been fully validated, a comprehensive understanding of the regulatory elements remains lacking. Moreover, there is little understanding of how t...

    Authors: Patrick M. Staunton, Aleksandra A. Miranda-CasoLuengo, Brendan J. Loftus and Isobel Claire Gormley

    Citation: BMC Bioinformatics 2019 20:466

    Content type: Research Article

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  25. Atomic force microscopy (AFM) allows the mechanical characterization of single cells and live tissue by quantifying force-distance (FD) data in nano-indentation experiments. One of the main problems when deali...

    Authors: Paul Müller, Shada Abuhattum, Stephanie Möllmert, Elke Ulbricht, Anna V. Taubenberger and Jochen Guck

    Citation: BMC Bioinformatics 2019 20:465

    Content type: Methodology article

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  26. The efficient biological production of industrially and economically important compounds is a challenging problem. Brute-force determination of the optimal pathways to efficient production of a target chemical...

    Authors: Leanne S. Whitmore, Bernard Nguyen, Ali Pinar, Anthe George and Corey M. Hudson

    Citation: BMC Bioinformatics 2019 20:461

    Content type: Software

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  27. Host immune response is coordinated by a variety of different specialized cell types that vary in time and location. While host immune response can be studied using conventional low-dimensional approaches, adv...

    Authors: Arezo Torang, Paraag Gupta and David J. Klinke II

    Citation: BMC Bioinformatics 2019 20:433

    Content type: Research article

    Published on:

  28. With the advent of array-based techniques to measure methylation levels in primary tumor samples, systematic investigations of methylomes have widely been performed on a large number of tumor entities. Most of...

    Authors: Pascal David Johann, Natalie Jäger, Stefan M. Pfister and Martin Sill

    Citation: BMC Bioinformatics 2019 20:428

    Content type: Methodology article

    Published on:

  29. Advances in medical technology have allowed for customized prognosis, diagnosis, and treatment regimens that utilize multiple heterogeneous data sources. Multiple kernel learning (MKL) is well suited for the i...

    Authors: Christopher M. Wilson, Kaiqiao Li, Xiaoqing Yu, Pei-Fen Kuan and Xuefeng Wang

    Citation: BMC Bioinformatics 2019 20:426

    Content type: Software

    Published on:

  30. Since the number of known lncRNA-disease associations verified by biological experiments is quite limited, it has been a challenging task to uncover human disease-related lncRNAs in recent years. Moreover, con...

    Authors: Jingwen Yu, Zhanwei Xuan, Xiang Feng, Quan Zou and Lei Wang

    Citation: BMC Bioinformatics 2019 20:396

    Content type: Research article

    Published on:

  31. Alkaloids, a class of organic compounds that contain nitrogen bases, are mainly synthesized as secondary metabolites in plants and fungi, and they have a wide range of bioactivities. Although there are thousan...

    Authors: Ryohei Eguchi, Naoaki Ono, Aki Hirai Morita, Tetsuo Katsuragi, Satoshi Nakamura, Ming Huang, Md. Altaf-Ul-Amin and Shigehiko Kanaya

    Citation: BMC Bioinformatics 2019 20:380

    Content type: Research article

    Published on:

  32. Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the da...

    Authors: Savvas Kinalis, Finn Cilius Nielsen, Ole Winther and Frederik Otzen Bagger

    Citation: BMC Bioinformatics 2019 20:379

    Content type: Methodology article

    Published on:

2018 Journal Metrics

  • Citation Impact
    2.511 - 2-year Impact Factor
    2.970 - 5-year Impact Factor
    0.855 - Source Normalized Impact per Paper (SNIP)
    1.374 - SCImago Journal Rank (SJR)

    Usage 
    4,129,368 downloads

    Social Media Impact
    4446 mentions

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