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Machine Learning and Artificial Intelligence in Bioinformatics

Page 4 of 4

  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. In spite of the abundance of genomic data, predictive models that describe phenotypes as a function of gene expression or mutations are difficult to obtain because they are affected by the curse of dimensional...

    Authors: Marina Esteban-Medina, María Peña-Chilet, Carlos Loucera and Joaquín Dopazo
    Citation: BMC Bioinformatics 2019 20:370
  15. Predicting meaningful miRNA-disease associations (MDAs) is costly. Therefore, an increasing number of researchers are beginning to focus on methods to predict potential MDAs. Thus, prediction methods with impr...

    Authors: Ying-Lian Gao, Zhen Cui, Jin-Xing Liu, Juan Wang and Chun-Hou Zheng
    Citation: BMC Bioinformatics 2019 20:353
  16. 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
  17. Although various machine learning-based predictors have been developed for estimating protein–protein interactions, their performances vary with dataset and species, and are affected by two primary aspects: ch...

    Authors: Kuan-Hsi Chen, Tsai-Feng Wang and Yuh-Jyh Hu
    Citation: BMC Bioinformatics 2019 20:308
  18. Representation learning provides new and powerful graph analytical approaches and tools for the highly valued data science challenge of mining knowledge graphs. Since previous graph analytical methods have mos...

    Authors: Zheng Gao, Gang Fu, Chunping Ouyang, Satoshi Tsutsui, Xiaozhong Liu, Jeremy Yang, Christopher Gessner, Brian Foote, David Wild, Ying Ding and Qi Yu
    Citation: BMC Bioinformatics 2019 20:306
  19. Modern molecular profiling techniques are yielding vast amounts of data from patient samples that could be utilized with machine learning methods to provide important biological insights and improvements in pa...

    Authors: Heinrich Roder, Carlos Oliveira, Lelia Net, Benjamin Linstid, Maxim Tsypin and Joanna Roder
    Citation: BMC Bioinformatics 2019 20:273
  20. Automatic extraction of chemical-disease relations (CDR) from unstructured text is of essential importance for disease treatment and drug development. Meanwhile, biomedical experts have built many highly-struc...

    Authors: Huiwei Zhou, Chengkun Lang, Zhuang Liu, Shixian Ning, Yingyu Lin and Lei Du
    Citation: BMC Bioinformatics 2019 20:260
  21. Computational approaches for the determination of biologically-active/native three-dimensional structures of proteins with novel sequences have to handle several challenges. The (conformation) space of possibl...

    Authors: Ahmed Bin Zaman and Amarda Shehu
    Citation: BMC Bioinformatics 2019 20:211
  22. Long non-coding RNAs play an important role in human complex diseases. Identification of lncRNA-disease associations will gain insight into disease-related lncRNAs and benefit disease diagnoses and treatment. ...

    Authors: Xiao-Nan Fan, Shao-Wu Zhang, Song-Yao Zhang, Kunju Zhu and Songjian Lu
    Citation: BMC Bioinformatics 2019 20:87
  23. Modern plant taxonomy reflects phylogenetic relationships among taxa based on proposed morphological and genetic similarities. However, taxonomical relation is not necessarily reflected by close overall resemb...

    Authors: Marco Seeland, Michael Rzanny, David Boho, Jana Wäldchen and Patrick Mäder
    Citation: BMC Bioinformatics 2019 20:4
  24. Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be ...

    Authors: Jie Hao, Youngsoon Kim, Tae-Kyung Kim and Mingon Kang
    Citation: BMC Bioinformatics 2018 19:510