Dr Jake Lever

  • Lecturer (School of Computing Science)

Biography

I am a Lecturer (Assistant Professor) in the Information, Data and Analysis section in the School of Computing Science. My research focuses on extracting biomedical knowledge from published research literature using different natural language processing and machine learning methods. This helps researchers to find important research knowledge and paves the way for representing biological knowledge computationally that artificial intelligence can reason on. I’ve focused in areas of precision medicine which tries to tailor treatment to an individual patient’s genetics and frequently relies on the latest research findings.

Before I moved to Glasgow, I spent two years at Stanford University as a postdoctoral researcher in the Helix Group. I received my Ph.D. in Bioinformatics from the University of British Columbia in Vancouver, Canada where I undertook research at Canada’s Michael Smith Genome Sciences Centre at BC Cancer. I completed my B.Eng. degree at the University of Edinburgh in Software Engineering.

Research interests

In Brief

  • Natural language processing, especially in biomedicine
  • Information extraction & retrieval
  • Knowledge bases & knowledge inference
  • Biomedical applications of machine learning
  • Bioinformatics & computational biology

In Detail

“Hey Siri, what drug should we try in our next clinical trial?” — a future doctor

There are many problems to solve before a computer could rationally answer that question. It would need to read and understand basic biomedical knowledge along with the latest research. It would need to be able to reason intelligently and balance the strength of evidence for different research ideas. Finally it would need to be able to explain itself clearly with substantial evidence, before any doctor or patient would consider taking an idea directly from an artificial intelligence. I am interested in chipping away at some of these problems to encourage researchers to use machine learning to read and work with the latest biomedical research.

I have initially focused on the first challenge of using machine learning to read biomedical research and extract knowledge. The vast scale of biomedical research is hard to comprehend and challenging to keep up with, especially for interdisciplinary researchers working across fields. Machine learning tools are absolutely necessary to help researchers digest the papers they need to read in order for them to develop new exciting research hypotheses.

Biomedical research relies heavily on databases of the latest biomedical knowledge kept in a structured, well-curated format. Unfortunately these are highly costly to maintain in terms of time and money. I have developed methods for building these databases directly from the literature (CancerMine) or to help database curators to find relevant papers themselves (CIViCmine and PGxMine). These resources have focused in the area of precision medicine, which predicts the best treatment for a patient given their unique genetics.

Research Projects | Google Scholar

Publications

List by: Type | Date

Jump to: 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2012
Number of items: 22.

2021

Lever, J. and Altman, R. B. (2021) Analyzing the vast coronavirus literature with CoronaCentral. Proceedings of the National Academy of Sciences of the United States of America, 118(23), 2100766118. (doi: 10.1073/pnas.2100766118) (PMID:34016708)

Wong, M., Previde, P., Cole, J., Thomas, B., Laxmeshwar, N., Mallory, E., Lever, J. , Petkovic, D., Altman, R. B. and Kulkarni, A. (2021) Search and visualization of gene-drug-disease interactions for pharmacogenomics and precision medicine research using GeneDive. Journal of Biomedical Informatics, 117, 103732. (doi: 10.1016/j.jbi.2021.103732) (PMID:33737208)

Sosa, D. N., Bimbin, C., Kaushal, A., Lavertu, A., Lever, J. , Rensi, S. and Altman, R. (2021) Repurposing biomedical informaticians for COVID-19. Journal of Biomedical Informatics, 115, 103673. (doi: 10.1016/j.jbi.2021.103673) (PMID:33486067) (PMCID:PMC7825863)

2020

Lever, J. , Altman, R. and Kim, J.-D. (2020) Extending TextAE for annotation of non-contiguous entities. Genomics and Informatics, 18(2), e15. (doi: 10.5808/gi.2020.18.2.e15) (PMID:32634869) (PMCID:PMC7362949)

Lever, J. , Barbarino, J. M., Gong, L., Huddart, R., Sangkuhl, K., Whaley, R., Whirl-Carrillo, M., Woon, M., Klein, T. E. and Altman, R. B. (2020) PGxMine: Text Mining for Curation of PharmGKB. In: 25th Pacific Symposium on Biocomputing, Puako, HI, USA, 03-07 Jan 2020, pp. 611-622.

2019

Lever, J. , Jones, M. R., Danos, A. M., Krysiak, K., Bonakdar, M., Grewal, J. K., Culibrk, L., Griffith, O. L., Griffith, M. and Jones, S. J.M. (2019) Text-mining clinically relevant cancer biomarkers for curation into the CIViC database. Genome Medicine, 11, 78. (doi: 10.1186/s13073-019-0686-y) (PMID:31796060) (PMCID:PMC6891984)

Chun, H.-J. E. et al. (2019) Identification and analyses of extra-cranial and cranial rhabdoid tumor molecular subgroups reveal tumors with cytotoxic T cell infiltration. Cell Reports, 29(8), 2338-2354.e7. (doi: 10.1016/j.celrep.2019.10.013) (PMID:31708418) (PMCID:PMC6905433)

Barbaian, A., Thompson, I. R., Lever, J. , Gagnier, L., Karimi, M. M. and Mager, D. L. (2019) LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq. Bioinformatics, 35(19), pp. 3839-3841. (doi: 10.1093/bioinformatics/btz130) (PMID:30793157)

Shen, Y. et al. (2019) Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments. Proceedings of the National Academy of Sciences of the United States of America, 116(38), pp. 19098-19108. (doi: 10.1073/pnas.1813495116) (PMID:31471491) (PMCID:PMC6754609)

Lever, J. , Zhao, E. Y., Grewal, J., Jones, M. R. and Jones, S. J.M. (2019) CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer. Nature Methods, 16(6), pp. 505-507. (doi: 10.1038/s41592-019-0422-y) (PMID:31110280)

2018

Lee, J. J.Y., Gottlieb, M. M., Lever, J. , Jones, S. J.M., Blau, N., van Karnebeek, C. D.M. and Wasserman, W. W. (2018) Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis. Journal of Inherited Metabolic Disease, 41(3), pp. 555-562. (doi: 10.1007/s10545-017-0125-4) (PMID:29340838) (PMCID:PMC5959948)

Lever, J. , Gakkhar, S., Gottlieb, M., Rashnavadi, T., Lin, S., Siu, C., Smith, M., Jones, M. R., Krzywinski, M. and Jones, S. J.M. (2018) A collaborative filtering-based approach to biomedical knowledge discovery. Bioinformatics, 34(4), pp. 652-659. (doi: 10.1093/bioinformatics/btx613) (PMID:29028901)

2017

Anekalla, K. R., Courneya, J.P., Florini, N., Lever, J. , Muchow, M. and Busby, B. (2017) PubRunner: a light-weight framework for updating text mining results. F1000Research, 6, 612. (doi: 10.12688/f1000research.11389.2) (PMID:29152221) (PMCID:PMC5664974)

Lever, J. , Krzywinski, M. and Altman, N. (2017) Principal component analysis. Nature Methods, 14(7), pp. 641-642. (doi: 10.1038/nmeth.4346)

2016

Lever, J. , Krzywinski, M. and Altman, N. (2016) Regularization. Nature Methods, 13(10), pp. 803-804. (doi: 10.1038/nmeth.4014)

Grinshtein, N. et al. (2016) Small molecule epigenetic screen identifies novel EZH2 and HDAC inhibitors that target glioblastoma brain tumor-initiating cells. Oncotarget, 7(37), pp. 59360-59376. (doi: 10.18632/oncotarget.10661) (PMID:27449082) (PMCID:PMC5312317)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Model selection and overfitting. Nature Methods, 13(9), pp. 703-704. (doi: 10.1038/nmeth.3968)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Classification evaluation. Nature Methods, 13(8), pp. 603-604. (doi: 10.1038/nmeth.3945)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Logistic regression. Nature Methods, 13(7), pp. 541-542. (doi: 10.1038/nmeth.3904)

Lever, J. , Jones, M. and Jones, S. J.M. (2016) CancerMine: Knowledge Base Construction for Personalised Cancer Treatment. In: 2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion (ICBO-BioCreative 2016), Corvallis, OR, USA, 01-04 Aug 2016,

2015

Davis, B., Shen, Y., Poon, C. C., Luchman, H. A., Stechishin, O. D., Pontifex, C. S., Wu, W., Kelly, J. J., Blough, M. D. and Terry Fox Research Institute Glioblastoma Consortium, (2015) Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors. Neuro-Oncology, 18(3), pp. 350-360. (doi: 10.1093/neuonc/nov143) (PMID:26245525) (PMCID:PMC4767234)

2012

Lever, J. and Komura, T. (2012) Real-time controllable fire using textured forces. Visual Computer, 28(6-8), pp. 691-700. (doi: 10.1007/s00371-012-0684-1)

This list was generated on Mon Sep 27 12:12:05 2021 BST.
Number of items: 22.

Articles

Lever, J. and Altman, R. B. (2021) Analyzing the vast coronavirus literature with CoronaCentral. Proceedings of the National Academy of Sciences of the United States of America, 118(23), 2100766118. (doi: 10.1073/pnas.2100766118) (PMID:34016708)

Wong, M., Previde, P., Cole, J., Thomas, B., Laxmeshwar, N., Mallory, E., Lever, J. , Petkovic, D., Altman, R. B. and Kulkarni, A. (2021) Search and visualization of gene-drug-disease interactions for pharmacogenomics and precision medicine research using GeneDive. Journal of Biomedical Informatics, 117, 103732. (doi: 10.1016/j.jbi.2021.103732) (PMID:33737208)

Sosa, D. N., Bimbin, C., Kaushal, A., Lavertu, A., Lever, J. , Rensi, S. and Altman, R. (2021) Repurposing biomedical informaticians for COVID-19. Journal of Biomedical Informatics, 115, 103673. (doi: 10.1016/j.jbi.2021.103673) (PMID:33486067) (PMCID:PMC7825863)

Lever, J. , Altman, R. and Kim, J.-D. (2020) Extending TextAE for annotation of non-contiguous entities. Genomics and Informatics, 18(2), e15. (doi: 10.5808/gi.2020.18.2.e15) (PMID:32634869) (PMCID:PMC7362949)

Lever, J. , Jones, M. R., Danos, A. M., Krysiak, K., Bonakdar, M., Grewal, J. K., Culibrk, L., Griffith, O. L., Griffith, M. and Jones, S. J.M. (2019) Text-mining clinically relevant cancer biomarkers for curation into the CIViC database. Genome Medicine, 11, 78. (doi: 10.1186/s13073-019-0686-y) (PMID:31796060) (PMCID:PMC6891984)

Chun, H.-J. E. et al. (2019) Identification and analyses of extra-cranial and cranial rhabdoid tumor molecular subgroups reveal tumors with cytotoxic T cell infiltration. Cell Reports, 29(8), 2338-2354.e7. (doi: 10.1016/j.celrep.2019.10.013) (PMID:31708418) (PMCID:PMC6905433)

Barbaian, A., Thompson, I. R., Lever, J. , Gagnier, L., Karimi, M. M. and Mager, D. L. (2019) LIONS: analysis suite for detecting and quantifying transposable element initiated transcription from RNA-seq. Bioinformatics, 35(19), pp. 3839-3841. (doi: 10.1093/bioinformatics/btz130) (PMID:30793157)

Shen, Y. et al. (2019) Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments. Proceedings of the National Academy of Sciences of the United States of America, 116(38), pp. 19098-19108. (doi: 10.1073/pnas.1813495116) (PMID:31471491) (PMCID:PMC6754609)

Lever, J. , Zhao, E. Y., Grewal, J., Jones, M. R. and Jones, S. J.M. (2019) CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer. Nature Methods, 16(6), pp. 505-507. (doi: 10.1038/s41592-019-0422-y) (PMID:31110280)

Lee, J. J.Y., Gottlieb, M. M., Lever, J. , Jones, S. J.M., Blau, N., van Karnebeek, C. D.M. and Wasserman, W. W. (2018) Text-based phenotypic profiles incorporating biochemical phenotypes of inborn errors of metabolism improve phenomics-based diagnosis. Journal of Inherited Metabolic Disease, 41(3), pp. 555-562. (doi: 10.1007/s10545-017-0125-4) (PMID:29340838) (PMCID:PMC5959948)

Lever, J. , Gakkhar, S., Gottlieb, M., Rashnavadi, T., Lin, S., Siu, C., Smith, M., Jones, M. R., Krzywinski, M. and Jones, S. J.M. (2018) A collaborative filtering-based approach to biomedical knowledge discovery. Bioinformatics, 34(4), pp. 652-659. (doi: 10.1093/bioinformatics/btx613) (PMID:29028901)

Anekalla, K. R., Courneya, J.P., Florini, N., Lever, J. , Muchow, M. and Busby, B. (2017) PubRunner: a light-weight framework for updating text mining results. F1000Research, 6, 612. (doi: 10.12688/f1000research.11389.2) (PMID:29152221) (PMCID:PMC5664974)

Lever, J. , Krzywinski, M. and Altman, N. (2017) Principal component analysis. Nature Methods, 14(7), pp. 641-642. (doi: 10.1038/nmeth.4346)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Regularization. Nature Methods, 13(10), pp. 803-804. (doi: 10.1038/nmeth.4014)

Grinshtein, N. et al. (2016) Small molecule epigenetic screen identifies novel EZH2 and HDAC inhibitors that target glioblastoma brain tumor-initiating cells. Oncotarget, 7(37), pp. 59360-59376. (doi: 10.18632/oncotarget.10661) (PMID:27449082) (PMCID:PMC5312317)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Model selection and overfitting. Nature Methods, 13(9), pp. 703-704. (doi: 10.1038/nmeth.3968)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Classification evaluation. Nature Methods, 13(8), pp. 603-604. (doi: 10.1038/nmeth.3945)

Lever, J. , Krzywinski, M. and Altman, N. (2016) Logistic regression. Nature Methods, 13(7), pp. 541-542. (doi: 10.1038/nmeth.3904)

Davis, B., Shen, Y., Poon, C. C., Luchman, H. A., Stechishin, O. D., Pontifex, C. S., Wu, W., Kelly, J. J., Blough, M. D. and Terry Fox Research Institute Glioblastoma Consortium, (2015) Comparative genomic and genetic analysis of glioblastoma-derived brain tumor-initiating cells and their parent tumors. Neuro-Oncology, 18(3), pp. 350-360. (doi: 10.1093/neuonc/nov143) (PMID:26245525) (PMCID:PMC4767234)

Lever, J. and Komura, T. (2012) Real-time controllable fire using textured forces. Visual Computer, 28(6-8), pp. 691-700. (doi: 10.1007/s00371-012-0684-1)

Conference Proceedings

Lever, J. , Barbarino, J. M., Gong, L., Huddart, R., Sangkuhl, K., Whaley, R., Whirl-Carrillo, M., Woon, M., Klein, T. E. and Altman, R. B. (2020) PGxMine: Text Mining for Curation of PharmGKB. In: 25th Pacific Symposium on Biocomputing, Puako, HI, USA, 03-07 Jan 2020, pp. 611-622.

Lever, J. , Jones, M. and Jones, S. J.M. (2016) CancerMine: Knowledge Base Construction for Personalised Cancer Treatment. In: 2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion (ICBO-BioCreative 2016), Corvallis, OR, USA, 01-04 Aug 2016,

This list was generated on Mon Sep 27 12:12:05 2021 BST.