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Machine learning for computational and systems biology

Section Editor: Professor Jean-Philippe Vert

As part of the launch of the journal section "Machine Learning and Artificial Intelligence in Bioinformatics", BMC Bioinformatics is excited to present a collection of papers included as part of the thematic series Machine learning for computational and systems biology.  

Neuer Inhalt © Pixabay

Papers included in this collection will appear below as they are published.

  1. Accumulated evidence shows that the abnormal regulation of long non-coding RNA (lncRNA) is associated with various human diseases. Accurately identifying disease-associated lncRNAs is helpful to study the mech...

    Authors: Dengju Yao, Xiaojuan Zhan, Xiaorong Zhan, Chee Keong Kwoh, Peng Li and Jinke Wang

    Citation: BMC Bioinformatics 2020 21:126

    Content type: Methodology article

    Published on:

  2. Both intra- and inter-sentential semantic relations in biomedical texts provide valuable information for biomedical research. However, most existing methods either focus on extracting intra-sentential relation...

    Authors: Zhiheng Li, Zhihao Yang, Yang Xiang, Ling Luo, Yuanyuan Sun and Hongfei Lin

    Citation: BMC Bioinformatics 2020 21:125

    Content type: Methodology article

    Published on:

  3. 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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  4. 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

    Published on:

  5. Glycans are complex sugar chains, crucial to many biological processes. By participating in binding interactions with proteins, glycans often play key roles in host–pathogen interactions. The specificities of ...

    Authors: Lachlan Coff, Jeffrey Chan, Paul A. Ramsland and Andrew J. Guy

    Citation: BMC Bioinformatics 2020 21:42

    Content type: Methodology Article

    Published on:

  6. 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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  7. 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

    Published on:

  8. 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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  9. In recent years, lncRNAs (long-non-coding RNAs) have been proved to be closely related to the occurrence and development of many serious diseases that are seriously harmful to human health. However, most of th...

    Authors: Jiechen Li, Xueyong Li, Xiang Feng, Bing Wang, Bihai Zhao and Lei Wang

    Citation: BMC Bioinformatics 2019 20:626

    Content type: Research article

    Published on:

  10. 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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  11. 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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  12. Recent advances in high-volume sequencing technology and mining of genomes from metagenomic samples call for rapid and reliable genome quality evaluation. The current release of the PATRIC database contains ov...

    Authors: Bruce Parrello, Rory Butler, Philippe Chlenski, Robert Olson, Jamie Overbeek, Gordon D. Pusch, Veronika Vonstein and Ross Overbeek

    Citation: BMC Bioinformatics 2019 20:486

    Content type: Database

    Published on:

  13. 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

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  14. 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

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  15. Modern genomic and proteomic profiling methods produce large amounts of data from tissue and blood-based samples that are of potential utility for improving patient care. However, the design of precision medic...

    Authors: Joanna Roder, Carlos Oliveira, Lelia Net, Maxim Tsypin, Benjamin Linstid and Heinrich Roder

    Citation: BMC Bioinformatics 2019 20:325

    Content type: Methodology article

    Published on: