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Volume 7 Supplement 1

Text mining for chemistry and the CHEMDNER track


Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. Articles have undergone the journal's standard peer review process.

  1. Natural language processing (NLP) and text mining technologies for the chemical domain (ChemNLP or chemical text mining) are key to improve the access and integration of information from unstructured data such as...

    Authors: Martin Krallinger, Florian Leitner, Obdulia Rabal, Miguel Vazquez, Julen Oyarzabal and Alfonso Valencia
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S1
  2. The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the a...

    Authors: Martin Krallinger, Obdulia Rabal, Florian Leitner, Miguel Vazquez, David Salgado, Zhiyong Lu, Robert Leaman, Yanan Lu, Donghong Ji, Daniel M Lowe, Roger A Sayle, Riza Theresa Batista-Navarro, Rafal Rak, Torsten Huber, Tim Rocktäschel, Sérgio Matos…
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S2
  3. The chemical compound and drug name recognition plays an important role in chemical text mining, and it is the basis for automatic relation extraction and event identification in chemical information processin...

    Authors: Yanan Lu, Donghong Ji, Xiaoyuan Yao, Xiaomei Wei and Xiaohui Liang
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S4
  4. The development of robust methods for chemical named entity recognition, a challenging natural language processing task, was previously hindered by the lack of publicly available, large-scale, gold standard co...

    Authors: Riza Batista-Navarro, Rafal Rak and Sophia Ananiadou
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S6
  5. Chemical compounds and drugs (together called chemical entities) embedded in scientific articles are crucial for many information extraction tasks in the biomedical domain. However, only a very limited number ...

    Authors: Buzhou Tang, Yudong Feng, Xiaolong Wang, Yonghui Wu, Yaoyun Zhang, Min Jiang, Jingqi Wang and Hua Xu
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S8
  6. Chemical and biomedical Named Entity Recognition (NER) is an essential prerequisite task before effective text mining can begin for biochemical-text data. Exploiting unlabeled text data to leverage system perf...

    Authors: Tsendsuren Munkhdalai, Meijing Li, Khuyagbaatar Batsuren, Hyeon Ah Park, Nak Hyeon Choi and Keun Ho Ryu
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S9
  7. The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstruct...

    Authors: Saber A Akhondi, Kristina M Hettne, Eelke van der Horst, Erik M van Mulligen and Jan A Kors
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S10
  8. In order to improve information access on chemical compounds and drugs (chemical entities) described in text repositories, it is very crucial to be able to identify chemical entity mentions (CEMs) automaticall...

    Authors: Shuo Xu, Xin An, Lijun Zhu, Yunliang Zhang and Haodong Zhang
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S11
  9. The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of rese...

    Authors: Hong-Jie Dai, Po-Ting Lai, Yung-Chun Chang and Richard Tzong-Han Tsai
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S14
  10. Small chemical molecules regulate biological processes at the molecular level. Those molecules are often involved in causing or treating pathological states. Automatically identifying such molecules in biomedi...

    Authors: Anabel Usié, Joaquim Cruz, Jorge Comas, Francesc Solsona and Rui Alves
    Citation: Journal of Cheminformatics 2015 7(Suppl 1):S15
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