Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Zhengqiao Zhao"'
Publikováno v:
Frontiers in Signal Processing, Vol 2 (2022)
Efficiently and accurately identifying which microbes are present in a biological sample is important to medicine and biology. For example, in medicine, microbe identification allows doctors to better diagnose diseases. Two questions are essential to
Externí odkaz:
https://doaj.org/article/39777fcd8e354b24b260be7cbe3960ed
Publikováno v:
Biology, Vol 11, Iss 12, p 1786 (2022)
Through the COVID-19 pandemic, SARS-CoV-2 has gained and lost multiple mutations in novel or unexpected combinations. Predicting how complex mutations affect COVID-19 disease severity is critical in planning public health responses as the virus conti
Externí odkaz:
https://doaj.org/article/5b2bca3479304780841f8e0f86b5efd1
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-23 (2020)
Abstract Background It is a computational challenge for current metagenomic classifiers to keep up with the pace of training data generated from genome sequencing projects, such as the exponentially-growing NCBI RefSeq bacterial genome database. When
Externí odkaz:
https://doaj.org/article/e847785e00c340b587bc1bd2e52b027b
Learning, visualizing and exploring 16S rRNA structure using an attention-based deep neural network.
Autor:
Zhengqiao Zhao, Stephen Woloszynek, Felix Agbavor, Joshua Chang Mell, Bahrad A Sokhansanj, Gail L Rosen
Publikováno v:
PLoS Computational Biology, Vol 17, Iss 9, p e1009345 (2021)
Recurrent neural networks with memory and attention mechanisms are widely used in natural language processing because they can capture short and long term sequential information for diverse tasks. We propose an integrated deep learning model for micr
Externí odkaz:
https://doaj.org/article/f942b69fd3b3444fabf60265b9f20db6
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 9, p e1008269 (2020)
We propose an efficient framework for genetic subtyping of SARS-CoV-2, the novel coronavirus that causes the COVID-19 pandemic. Efficient viral subtyping enables visualization and modeling of the geographic distribution and temporal dynamics of disea
Externí odkaz:
https://doaj.org/article/7da8b870b3354a418db5beb5f2a0ce0b
Autor:
Chad M. Cullen, Kawalpreet K. Aneja, Sinem Beyhan, Clara E. Cho, Stephen Woloszynek, Matteo Convertino, Sophie J. McCoy, Yanyan Zhang, Matthew Z. Anderson, David Alvarez-Ponce, Ekaterina Smirnova, Lisa Karstens, Pieter C. Dorrestein, Hongzhe Li, Ananya Sen Gupta, Kevin Cheung, Jennifer Gloeckner Powers, Zhengqiao Zhao, Gail L. Rosen
Publikováno v:
Frontiers in Microbiology, Vol 11 (2020)
Microbiome research has increased dramatically in recent years, driven by advances in technology and significant reductions in the cost of analysis. Such research has unlocked a wealth of data, which has yielded tremendous insight into the nature of
Externí odkaz:
https://doaj.org/article/f19f85a53f544e10812aa4297fe68792
Publikováno v:
PLoS Computational Biology, Vol 15, Iss 2, p e1006721 (2019)
Advances in high-throughput sequencing have increased the availability of microbiome sequencing data that can be exploited to characterize microbiome community structure in situ. We explore using word and sentence embedding approaches for nucleotide
Externí odkaz:
https://doaj.org/article/f00a15dce39c4a88b7ef70d1085460f2
Autor:
Stephen Woloszynek, Joshua Chang Mell, Zhengqiao Zhao, Gideon Simpson, Michael P O'Connor, Gail L Rosen
Publikováno v:
PLoS ONE, Vol 14, Iss 12, p e0219235 (2019)
Analysis of microbiome data involves identifying co-occurring groups of taxa associated with sample features of interest (e.g., disease state). Elucidating such relations is often difficult as microbiome data are compositional, sparse, and have high
Externí odkaz:
https://doaj.org/article/ef999a91eeed40d1b53c3801e3acb399
Publikováno v:
Biology, Vol 9, Iss 11, p 365 (2020)
Machine learning algorithms can learn mechanisms of antimicrobial resistance from the data of DNA sequence without any a priori information. Interpreting a trained machine learning algorithm can be exploited for validating the model and obtaining new
Externí odkaz:
https://doaj.org/article/6706ff1a47904f7291135c6005a61d06
Autor:
Fernando Meyer, Adrian Fritz, Zhi-Luo Deng, David Koslicki, Till Robin Lesker, Alexey Gurevich, Gary Robertson, Mohammed Alser, Dmitry Antipov, Francesco Beghini, Denis Bertrand, Jaqueline J. Brito, C. Titus Brown, Jan Buchmann, Aydin Buluç, Bo Chen, Rayan Chikhi, Philip T. L. C. Clausen, Alexandru Cristian, Piotr Wojciech Dabrowski, Aaron E. Darling, Rob Egan, Eleazar Eskin, Evangelos Georganas, Eugene Goltsman, Melissa A. Gray, Lars Hestbjerg Hansen, Steven Hofmeyr, Pingqin Huang, Luiz Irber, Huijue Jia, Tue Sparholt Jørgensen, Silas D. Kieser, Terje Klemetsen, Axel Kola, Mikhail Kolmogorov, Anton Korobeynikov, Jason Kwan, Nathan LaPierre, Claire Lemaitre, Chenhao Li, Antoine Limasset, Fabio Malcher-Miranda, Serghei Mangul, Vanessa R. Marcelino, Camille Marchet, Pierre Marijon, Dmitry Meleshko, Daniel R. Mende, Alessio Milanese, Niranjan Nagarajan, Jakob Nissen, Sergey Nurk, Leonid Oliker, Lucas Paoli, Pierre Peterlongo, Vitor C. Piro, Jacob S. Porter, Simon Rasmussen, Evan R. Rees, Knut Reinert, Bernhard Renard, Espen Mikal Robertsen, Gail L. Rosen, Hans-Joachim Ruscheweyh, Varuni Sarwal, Nicola Segata, Enrico Seiler, Lizhen Shi, Fengzhu Sun, Shinichi Sunagawa, Søren Johannes Sørensen, Ashleigh Thomas, Chengxuan Tong, Mirko Trajkovski, Julien Tremblay, Gherman Uritskiy, Riccardo Vicedomini, Zhengyang Wang, Ziye Wang, Zhong Wang, Andrew Warren, Nils Peder Willassen, Katherine Yelick, Ronghui You, Georg Zeller, Zhengqiao Zhao, Shanfeng Zhu, Jie Zhu, Ruben Garrido-Oter, Petra Gastmeier, Stephane Hacquard, Susanne Häußler, Ariane Khaledi, Friederike Maechler, Fantin Mesny, Simona Radutoiu, Paul Schulze-Lefert, Nathiana Smit, Till Strowig, Andreas Bremges, Alexander Sczyrba, Alice Carolyn McHardy
Publikováno v:
Nature Methods
Meyer, F, Fritz, A, Deng, Z L, Koslicki, D, Lesker, T R, Gurevich, A, Robertson, G, Alser, M, Antipov, D, Beghini, F, Bertrand, D, Brito, J J, Brown, C T, Buchmann, J, Buluç, A, Chen, B, Chikhi, R, Clausen, P T L C, Cristian, A, Dabrowski, P W, Darling, A E, Egan, R, Eskin, E, Georganas, E, Goltsman, E, Gray, M A, Hansen, L H, Hofmeyr, S, Huang, P, Irber, L, Jia, H, Jørgensen, T S, Kieser, S D, Klemetsen, T, Kola, A, Kolmogorov, M, Korobeynikov, A, Kwan, J, LaPierre, N, Lemaitre, C, Li, C, Limasset, A, Malcher-Miranda, F, Mangul, S, Marcelino, V R, Marchet, C, Marijon, P, Meleshko, D, Mende, D R, Milanese, A, Nagarajan, N, Nissen, J, Nurk, S, Oliker, L, Paoli, L, Peterlongo, P, Piro, V C, Porter, J S, Rasmussen, S, Rees, E R, Reinert, K, Renard, B, Robertsen, E M, Rosen, G L, Ruscheweyh, H J, Sarwal, V, Segata, N, Seiler, E, Shi, L, Sun, F, Sunagawa, S, Sørensen, S J, Thomas, A, Tong, C, Trajkovski, M, Tremblay, J, Uritskiy, G, Vicedomini, R, Wang, Z, Wang, Z, Wang, Z, Warren, A, Willassen, N P, Yelick, K, You, R, Zeller, G, Zhao, Z, Zhu, S, Zhu, J, Garrido-Oter, R, Gastmeier, P, Hacquard, S, Häußler, S, Khaledi, A, Maechler, F, Mesny, F, Radutoiu, S, Schulze-Lefert, P, Smit, N, Strowig, T, Bremges, A, Sczyrba, A & McHardy, A C 2022, ' Critical Assessment of Metagenome Interpretation : the second round of challenges ', Nature Methods, vol. 19, no. 4, pp. 429-440 . https://doi.org/10.1038/s41592-022-01431-4
Nature Methods, 2022, 19 (4), pp.429-440. ⟨10.1038/s41592-022-01431-4⟩
Nature methods, 19(4), 429-440. Nature Publishing Group
Meyer, F, Fritz, A, Deng, Z-L, Koslicki, D, Lesker, T R, Gurevich, A, Robertson, G, Alser, M, Antipov, D, Beghini, F, Bertrand, D, Brito, J J, Brown, C T, Buchmann, J, Buluç, A, Chen, B, Chikhi, R, Clausen, P T L C, Cristian, A, Dabrowski, P W, Darling, A E, Egan, R, Eskin, E, Georganas, E, Goltsman, E, Gray, M A, Hansen, L H, Hofmeyr, S, Huang, P, Irber, L, Jia, H, Jørgensen, T S, Kieser, S D, Klemetsen, T, Kola, A, Kolmogorov, M, Korobeynikov, A, Kwan, J, LaPierre, N, Lemaitre, C, Li, C, Limasset, A, Malcher-Miranda, F, Mangul, S, Marcelino, V R, Marchet, C, Marijon, P, Meleshko, D, Mende, D R, Milanese, A, Nagarajan, N, Nissen, J, Nurk, S, Oliker, L, Paoli, L, Peterlongo, P, Piro, V C, Porter, J S, Rasmussen, S, Rees, E R, Reinert, K, Renard, B, Robertsen, E M, Rosen, G L, Ruscheweyh, H-J, Sarwal, V, Segata, N, Seiler, E, Shi, L, Sun, F, Sunagawa, S, Sørensen, S J, Thomas, A, Tong, C, Trajkovski, M, Tremblay, J, Uritskiy, G, Vicedomini, R, Wang, Z, Wang, Z, Wang, Z, Warren, A, Willassen, N P, Yelick, K, You, R, Zeller, G, Zhao, Z, Zhu, S, Zhu, J, Garrido-Oter, R, Gastmeier, P, Hacquard, S, Häußler, S, Khaledi, A, Maechler, F, Mesny, F, Radutoiu, S, Schulze-Lefert, P, Smit, N, Strowig, T, Bremges, A, Sczyrba, A & McHardy, A C 2022, ' Critical Assessment of Metagenome Interpretation : the second round of challenges ', Nature Methods, vol. 19, no. 4, pp. 429-440 . https://doi.org/10.1038/s41592-022-01431-4
Nature Methods, 19 (8)
Meyer, F, Fritz, A, Deng, Z L, Koslicki, D, Lesker, T R, Gurevich, A, Robertson, G, Alser, M, Antipov, D, Beghini, F, Bertrand, D, Brito, J J, Brown, C T, Buchmann, J, Buluç, A, Chen, B, Chikhi, R, Clausen, P T L C, Cristian, A, Dabrowski, P W, Darling, A E, Egan, R, Eskin, E, Georganas, E, Goltsman, E, Gray, M A, Hansen, L H, Hofmeyr, S, Huang, P, Irber, L, Jia, H, Jørgensen, T S, Kieser, S D, Klemetsen, T, Kola, A, Kolmogorov, M, Korobeynikov, A, Kwan, J, LaPierre, N, Lemaitre, C, Li, C, Limasset, A, Malcher-Miranda, F, Mangul, S, Marcelino, V R, Marchet, C, Marijon, P, Meleshko, D, Mende, D R, Milanese, A, Nagarajan, N, Nissen, J, Nurk, S, Oliker, L, Paoli, L, Peterlongo, P, Piro, V C, Porter, J S, Rasmussen, S, Rees, E R, Reinert, K, Renard, B, Robertsen, E M, Rosen, G L, Ruscheweyh, H J, Sarwal, V, Segata, N, Seiler, E, Shi, L, Sun, F, Sunagawa, S, Sørensen, S J, Thomas, A, Tong, C, Trajkovski, M, Tremblay, J, Uritskiy, G, Vicedomini, R, Wang, Z, Wang, Z, Wang, Z, Warren, A, Willassen, N P, Yelick, K, You, R, Zeller, G, Zhao, Z, Zhu, S, Zhu, J, Garrido-Oter, R, Gastmeier, P, Hacquard, S, Häußler, S, Khaledi, A, Maechler, F, Mesny, F, Radutoiu, S, Schulze-Lefert, P, Smit, N, Strowig, T, Bremges, A, Sczyrba, A & McHardy, A C 2022, ' Critical Assessment of Metagenome Interpretation : the second round of challenges ', Nature Methods, vol. 19, no. 4, pp. 429-440 . https://doi.org/10.1038/s41592-022-01431-4
Nature Methods, 2022, 19 (4), pp.429-440. ⟨10.1038/s41592-022-01431-4⟩
Nature methods, 19(4), 429-440. Nature Publishing Group
Meyer, F, Fritz, A, Deng, Z-L, Koslicki, D, Lesker, T R, Gurevich, A, Robertson, G, Alser, M, Antipov, D, Beghini, F, Bertrand, D, Brito, J J, Brown, C T, Buchmann, J, Buluç, A, Chen, B, Chikhi, R, Clausen, P T L C, Cristian, A, Dabrowski, P W, Darling, A E, Egan, R, Eskin, E, Georganas, E, Goltsman, E, Gray, M A, Hansen, L H, Hofmeyr, S, Huang, P, Irber, L, Jia, H, Jørgensen, T S, Kieser, S D, Klemetsen, T, Kola, A, Kolmogorov, M, Korobeynikov, A, Kwan, J, LaPierre, N, Lemaitre, C, Li, C, Limasset, A, Malcher-Miranda, F, Mangul, S, Marcelino, V R, Marchet, C, Marijon, P, Meleshko, D, Mende, D R, Milanese, A, Nagarajan, N, Nissen, J, Nurk, S, Oliker, L, Paoli, L, Peterlongo, P, Piro, V C, Porter, J S, Rasmussen, S, Rees, E R, Reinert, K, Renard, B, Robertsen, E M, Rosen, G L, Ruscheweyh, H-J, Sarwal, V, Segata, N, Seiler, E, Shi, L, Sun, F, Sunagawa, S, Sørensen, S J, Thomas, A, Tong, C, Trajkovski, M, Tremblay, J, Uritskiy, G, Vicedomini, R, Wang, Z, Wang, Z, Wang, Z, Warren, A, Willassen, N P, Yelick, K, You, R, Zeller, G, Zhao, Z, Zhu, S, Zhu, J, Garrido-Oter, R, Gastmeier, P, Hacquard, S, Häußler, S, Khaledi, A, Maechler, F, Mesny, F, Radutoiu, S, Schulze-Lefert, P, Smit, N, Strowig, T, Bremges, A, Sczyrba, A & McHardy, A C 2022, ' Critical Assessment of Metagenome Interpretation : the second round of challenges ', Nature Methods, vol. 19, no. 4, pp. 429-440 . https://doi.org/10.1038/s41592-022-01431-4
Nature Methods, 19 (8)
Evaluating metagenomic software is key for optimizing metagenome interpretation and focus of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). The CAMI II challenge engaged the community to assess methods on realistic an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6a457600da700f14909805684c3378a
https://hdl.handle.net/10453/163369
https://hdl.handle.net/10453/163369