51
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Santibáñez R, Garrido D, Martin AJM. Pleione: A tool for statistical and multi-objective calibration of Rule-based models. Sci Rep 2019; 9:15104. [PMID: 31641245 PMCID: PMC6805871 DOI: 10.1038/s41598-019-51546-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 09/24/2019] [Indexed: 11/17/2022] Open
Abstract
Mathematical models based on Ordinary Differential Equations (ODEs) are frequently used to describe and simulate biological systems. Nevertheless, such models are often difficult to understand. Unlike ODE models, Rule-Based Models (RBMs) utilise formal language to describe reactions as a cumulative number of statements that are easier to understand and correct. They are also gaining popularity because of their conciseness and simulation flexibility. However, RBMs generally lack tools to perform further analysis that requires simulation. This situation arises because exact and approximate simulations are computationally intensive. Translating RBMs into ODEs is commonly used to reduce simulation time, but this technique may be prohibitive due to combinatorial explosion. Here, we present the software called Pleione to calibrate RBMs. Parameter calibration is essential given the incomplete experimental determination of reaction rates and the goal of using models to reproduce experimental data. The software distributes stochastic simulations and calculations and incorporates equivalence tests to determine the fitness of RBMs compared with data. The primary features of Pleione were thoroughly tested on a model of gene regulation in Escherichia coli. Pleione yielded satisfactory results regarding calculation time and error reduction for multiple simulators, models, parameter search strategies, and computing infrastructures.
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Affiliation(s)
- Rodrigo Santibáñez
- Network Biology Lab, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, 8580745, Chile
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, 7820436, Chile
| | - Daniel Garrido
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, 7820436, Chile
| | - Alberto J M Martin
- Network Biology Lab, Centro de Genómica y Bioinformática, Facultad de Ciencias, Universidad Mayor, Santiago, 8580745, Chile.
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52
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Gophna U. The unbearable ease of expression-how avoidance of spurious transcription can shape G+C content in bacterial genomes. FEMS Microbiol Lett 2019; 365:5181332. [PMID: 30423131 DOI: 10.1093/femsle/fny267] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 11/11/2018] [Indexed: 12/28/2022] Open
Affiliation(s)
- Uri Gophna
- Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Levanon Street, Tel Aviv 69000, Israel
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53
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Nora LC, Westmann CA, Guazzaroni ME, Siddaiah C, Gupta VK, Silva-Rocha R. Recent advances in plasmid-based tools for establishing novel microbial chassis. Biotechnol Adv 2019; 37:107433. [PMID: 31437573 DOI: 10.1016/j.biotechadv.2019.107433] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 07/11/2019] [Accepted: 08/16/2019] [Indexed: 12/28/2022]
Abstract
A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with "build-your-own" microbial host.
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Affiliation(s)
- Luísa Czamanski Nora
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - Cauã Antunes Westmann
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - María-Eugenia Guazzaroni
- Faculty of Philosophy, Science and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | | | - Vijai Kumar Gupta
- ERA Chair of Green Chemistry, Department of Chemistry and Biotechnology, School of Science, Tallinn University of Technology, 12618 Tallinn, Estonia
| | - Rafael Silva-Rocha
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil.
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54
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Yim SS, Johns NI, Park J, Gomes ALC, McBee RM, Richardson M, Ronda C, Chen SP, Garenne D, Noireaux V, Wang HH. Multiplex transcriptional characterizations across diverse bacterial species using cell-free systems. Mol Syst Biol 2019; 15:e8875. [PMID: 31464371 PMCID: PMC6692573 DOI: 10.15252/msb.20198875] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 07/01/2019] [Accepted: 07/03/2019] [Indexed: 12/14/2022] Open
Abstract
Cell-free expression systems enable rapid prototyping of genetic programs in vitro. However, current throughput of cell-free measurements is limited by the use of channel-limited fluorescent readouts. Here, we describe DNA Regulatory element Analysis by cell-Free Transcription and Sequencing (DRAFTS), a rapid and robust in vitro approach for multiplexed measurement of transcriptional activities from thousands of regulatory sequences in a single reaction. We employ this method in active cell lysates developed from ten diverse bacterial species. Interspecies analysis of transcriptional profiles from > 1,000 diverse regulatory sequences reveals functional differences in promoter activity that can be quantitatively modeled, providing a rich resource for tuning gene expression in diverse bacterial species. Finally, we examine the transcriptional capacities of dual-species hybrid lysates that can simultaneously harness gene expression properties of multiple organisms. We expect that this cell-free multiplex transcriptional measurement approach will improve genetic part prototyping in new bacterial chassis for synthetic biology.
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Affiliation(s)
- Sung Sun Yim
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
| | - Nathan I Johns
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
- Present address:
Department of BioengineeringStanford UniversityStanfordCAUSA
| | - Jimin Park
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - Antonio LC Gomes
- Department of ImmunologyMemorial Sloan Kettering Cancer CenterNew YorkNYUSA
| | - Ross M McBee
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Department of Biological SciencesColumbia UniversityNew YorkNYUSA
| | - Miles Richardson
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - Carlotta Ronda
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
| | - Sway P Chen
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Integrated Program in Cellular, Molecular, and Biomedical StudiesColumbia UniversityNew YorkNYUSA
| | - David Garenne
- School of Physics and AstronomyUniversity of MinnesotaMinneapolisMNUSA
| | - Vincent Noireaux
- School of Physics and AstronomyUniversity of MinnesotaMinneapolisMNUSA
| | - Harris H Wang
- Department of Systems BiologyColumbia UniversityNew YorkNYUSA
- Department of Pathology and Cell BiologyColumbia UniversityNew YorkNYUSA
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55
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Gilman J, Singleton C, Tennant RK, James P, Howard TP, Lux T, Parker DA, Love J. Rapid, Heuristic Discovery and Design of Promoter Collections in Non-Model Microbes for Industrial Applications. ACS Synth Biol 2019; 8:1175-1186. [PMID: 30995831 DOI: 10.1021/acssynbio.9b00061] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Well-characterized promoter collections for synthetic biology applications are not always available in industrially relevant hosts. We developed a broadly applicable method for promoter identification in atypical microbial hosts that requires no a priori understanding of cis-regulatory element structure. This novel approach combines bioinformatic filtering with rapid empirical characterization to expand the promoter toolkit and uses machine learning to improve the understanding of the relationship between DNA sequence and function. Here, we apply the method in Geobacillus thermoglucosidasius, a thermophilic organism with high potential as a synthetic biology chassis for industrial applications. Bioinformatic screening of G. kaustophilus, G. stearothermophilus, G. thermodenitrificans, and G. thermoglucosidasius resulted in the identification of 636 100 bp putative promoters, encompassing the genome-wide design space and lacking known transcription factor binding sites. Eighty of these sequences were characterized in vivo, and activities covered a 2-log range of predictable expression levels. Seven sequences were shown to function consistently regardless of the downstream coding sequence. Partition modeling identified sequence positions upstream of the canonical -35 and -10 consensus motifs that were predicted to strongly influence regulatory activity in Geobacillus, and artificial neural network and partial least squares regression models were derived to assess if there were a simple, forward, quantitative method for in silico prediction of promoter function. However, the models were insufficiently general to predict pre hoc promoter activity in vivo, most probably as a result of the relatively small size of the training data set compared to the size of the modeled design space.
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Affiliation(s)
- James Gilman
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Chloe Singleton
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Richard K. Tennant
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Paul James
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Thomas P. Howard
- School of Natural and Environmental Sciences, Newcastle University, Devonshire Building, Newcastle-upon-Tyne NE1 7RU, U.K
| | - Thomas Lux
- Plant Genome and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich 85764, Germany
| | - David A. Parker
- Biodomain, Shell Technology Center Houston, 3333 Highway 6 South, Houston, Texas 77082-3101, United States
| | - John Love
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
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56
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Kinney JB, McCandlish DM. Massively Parallel Assays and Quantitative Sequence-Function Relationships. Annu Rev Genomics Hum Genet 2019; 20:99-127. [PMID: 31091417 DOI: 10.1146/annurev-genom-083118-014845] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and cis-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.
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Affiliation(s)
- Justin B Kinney
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA; ,
| | - David M McCandlish
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA; ,
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57
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Brave new ‘RNA’ world—advances in RNA tools and their application for understanding and engineering biological systems. ACTA ACUST UNITED AC 2019. [DOI: 10.1016/j.coisb.2019.02.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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58
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Schubert B, Maddamsetti R, Nyman J, Farhat MR, Marks DS. Genome-wide discovery of epistatic loci affecting antibiotic resistance in Neisseria gonorrhoeae using evolutionary couplings. Nat Microbiol 2018; 4:328-338. [PMID: 30510172 DOI: 10.1038/s41564-018-0309-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 10/26/2018] [Indexed: 11/09/2022]
Abstract
Genome analysis should allow the discovery of interdependent loci that together cause antibiotic resistance. In practice, however, the vast number of possible epistatic interactions erodes statistical power. Here, we extend an approach that has been successfully used to identify epistatic residues in proteins to infer genomic loci that are strongly coupled. This approach reduces the number of tests required for an epistatic genome-wide association study of antibiotic resistance and increases the likelihood of identifying causal epistasis. We discovered 38 loci and 240 epistatic pairs that influence the minimum inhibitory concentrations of 5 different antibiotics in 1,102 isolates of Neisseria gonorrhoeae that were confirmed in a second dataset of 495 isolates. Many known resistance-affecting loci were recovered; however, the majority of associations occurred in unreported genes, such as murE. About half of the discovered epistasis involved at least one locus previously associated with antibiotic resistance, including interactions between gyrA and parC. Still, many combinations involved unreported loci and genes. While most variation in minimum inhibitory concentrations could be explained by identified loci, epistasis substantially increased explained phenotypic variance. Our work provides a systematic identification of epistasis affecting antibiotic resistance in N. gonorrhoeae and a generalizable approach for epistatic genome-wide association studies.
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Affiliation(s)
- Benjamin Schubert
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.,Department of Cell Biology, Harvard Medical School, Boston, MA, USA.,cBio Center, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Rohan Maddamsetti
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA.,Department of Biological Sciences, Old Dominion University, Norfolk, VA, USA
| | - Jackson Nyman
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Maha R Farhat
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Debora S Marks
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA. .,Broad Institute of Harvard and MIT, Cambridge, MA, USA.
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59
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Alves LDF, Westmann CA, Lovate GL, de Siqueira GMV, Borelli TC, Guazzaroni ME. Metagenomic Approaches for Understanding New Concepts in Microbial Science. Int J Genomics 2018; 2018:2312987. [PMID: 30211213 PMCID: PMC6126073 DOI: 10.1155/2018/2312987] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Revised: 06/21/2018] [Accepted: 07/29/2018] [Indexed: 12/15/2022] Open
Abstract
Over the past thirty years, since the dawn of metagenomic studies, a completely new (micro) universe was revealed, with the potential to have profound impacts on many aspects of the society. Remarkably, the study of human microbiome provided a new perspective on a myriad of human traits previously regarded as solely (epi-) genetically encoded, such as disease susceptibility, immunological response, and social and nutritional behaviors. In this context, metagenomics has established a powerful framework for understanding the intricate connections between human societies and microbial communities, ultimately allowing for the optimization of both human health and productivity. Thus, we have shifted from the old concept of microbes as harmful organisms to a broader panorama, in which the signal of the relationship between humans and microbes is flexible and directly dependent on our own decisions and practices. In parallel, metagenomics has also been playing a major role in the prospection of "hidden" genetic features and the development of biotechnological applications, through the discovery of novel genes, enzymes, pathways, and bioactive molecules with completely new or improved biochemical functions. Therefore, this review highlights the major milestones over the last three decades of metagenomics, providing insights into both its potentialities and current challenges.
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Affiliation(s)
- Luana de Fátima Alves
- Department of Biochemistry, Faculdade de Medicina de Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Cauã Antunes Westmann
- Department of Cell Biology, Faculdade de Medicina de Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - Gabriel Lencioni Lovate
- Department of Biochemistry, Faculdade de Medicina de Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | | | - Tiago Cabral Borelli
- Department of Biology, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
| | - María-Eugenia Guazzaroni
- Department of Biology, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, University of São Paulo, Ribeirão Preto, SP, Brazil
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60
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Ji CH, Kim JP, Kang HS. Library of Synthetic Streptomyces Regulatory Sequences for Use in Promoter Engineering of Natural Product Biosynthetic Gene Clusters. ACS Synth Biol 2018; 7:1946-1955. [PMID: 29966097 DOI: 10.1021/acssynbio.8b00175] [Citation(s) in RCA: 44] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Promoter engineering has emerged as a powerful tool to activate transcriptionally silent natural product biosynthetic gene clusters found in bacterial genomes. Since biosynthetic gene clusters are composed of multiple operons, their promoter engineering requires the use of a set of regulatory sequences with a similar level of activities. Although several successful examples of promoter engineering have been reported, its widespread use has been limited due to the lack of a library of regulatory sequences suitable for use in promoter engineering of large, multiple operon-containing biosynthetic gene clusters. Here, we present the construction of a library of constitutively active, synthetic Streptomyces regulatory sequences. The promoter assay system has been developed using a single-module nonribosomal peptide synthetase that produces the peptide blue pigment indigoidine, allowing for the rapid screening of a large pool of regulatory sequences. The highly randomized regulatory sequences in both promoter and ribosome binding site regions were screened for their ability to produce the blue pigment, and they are classified into the strong, medium, and weak regulatory sequences based on the strength of a blue color. We demonstrated the utility of our synthetic regulatory sequences for promoter engineering of natural product biosynthetic gene clusters using the actinorhodin gene cluster as a model cluster. We believe that the set of Streptomyces regulatory sequences we report here will facilitate the discovery of new natural products from silent, cryptic biosynthetic gene clusters found in sequenced Streptomyces genomes.
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Affiliation(s)
- Chang-Hun Ji
- Department of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Korea
| | - Jong-Pyung Kim
- Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Chungbuk 28116, Korea
| | - Hahk-Soo Kang
- Department of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Korea
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61
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Harris Wang. Nat Methods 2018. [DOI: 10.1038/nmeth.4676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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