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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. 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

    Published on:

  2. 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:

  3. 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

    Published on:

  4. 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:

  5. 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

    Published on:

  6. 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

    Published on:

  7. 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:

  8. 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:

  9. 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:

  10. 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: