The Experts below are selected from a list of 1317 Experts worldwide ranked by ideXlab platform
Gil Alterovitz - One of the best experts on this subject based on the ideXlab platform.
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Biobrick chain recommendations for genetic circuit design
Computers in biology and medicine, 2017Co-Authors: Jiaoyun Yang, Bowen Gong, Gil AlterovitzAbstract:Synthetic biology databases have collected numerous Biobricks to accelerate genetic circuit design. However, selecting Biobricks is a tough task. Here, we leverage the fact that these manually designed circuits can provide underlying knowledge to support biobrick selection. We propose to design a recommendation system based on the analysis of available genetic circuits, which can narrow down the biobrick selection range and provide candidate Biobricks for users to choose. A recommendation strategy based on a Markov model is established to tackle this issue. Furthermore, a biobrick chain recommendation algorithm Sira is proposed that applies a dynamic programming process on a layered state transition graph to obtain the top k recommendation results. In addition, a weighted filtering strategy, WFSira, is proposed to augment the performance of Sira. The experimental results on the Registry of Standard Biological Parts show that Sira outperforms other algorithms significantly for biobrick recommendations, with approximately 30% improvement in terms of recall rate. It is also able to make biobrick chain recommendations. WFSira can further improve the recall rate of Sira by an average of 7.5% for the top 5 recommendations.
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Nonlinear dimensionality reduction methods for synthetic biology Biobricks' visualization.
BMC bioinformatics, 2017Co-Authors: Jiaoyun Yang, Haipeng Wang, Huitong Ding, Gil AlterovitzAbstract:Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize Biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on Biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting Biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of Biobricks are tested. The visualization graphs illustrate discriminated Biobricks and inappropriately labeled Biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate Biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of Biobricks could be discriminated and inappropriately labeled Biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases’ quality, and make Biobricks selection.
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Additional file 1 of Nonlinear dimensionality reduction methods for synthetic biology Biobricksâ visualization
2017Co-Authors: Jiaoyun Yang, Haipeng Wang, Huitong Ding, Gil AlterovitzAbstract:This file contains more experiments on other types of Biobricks. Besides, classification validation for the dimensionality reduction results are also included. These results are illustrated in two figures and two tables in the file. Figure S1: Dimensionality reduction results for various combinations of Plasmid backbones, Promoters, Terminators, Translational units, Protein generators, Primers by applying Isomap algorithm. Figure S2: Dimensionality reduction results for various combinations of Plasmid backbones, Promoters, Terminators, Translational units, Protein generators, Primers by applying Laplacian Eigenmaps algorithm. Table S1: Clustering accuracy comparison of dimensionality reduction results in Figures S1 and S2. Table S2: Classification accuracy comparison of dimensionality reduction results by Isomap and Laplacian Eigenmaps. (PDF 123 kb
Jiaoyun Yang - One of the best experts on this subject based on the ideXlab platform.
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Biobrick chain recommendations for genetic circuit design
Computers in biology and medicine, 2017Co-Authors: Jiaoyun Yang, Bowen Gong, Gil AlterovitzAbstract:Synthetic biology databases have collected numerous Biobricks to accelerate genetic circuit design. However, selecting Biobricks is a tough task. Here, we leverage the fact that these manually designed circuits can provide underlying knowledge to support biobrick selection. We propose to design a recommendation system based on the analysis of available genetic circuits, which can narrow down the biobrick selection range and provide candidate Biobricks for users to choose. A recommendation strategy based on a Markov model is established to tackle this issue. Furthermore, a biobrick chain recommendation algorithm Sira is proposed that applies a dynamic programming process on a layered state transition graph to obtain the top k recommendation results. In addition, a weighted filtering strategy, WFSira, is proposed to augment the performance of Sira. The experimental results on the Registry of Standard Biological Parts show that Sira outperforms other algorithms significantly for biobrick recommendations, with approximately 30% improvement in terms of recall rate. It is also able to make biobrick chain recommendations. WFSira can further improve the recall rate of Sira by an average of 7.5% for the top 5 recommendations.
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Nonlinear dimensionality reduction methods for synthetic biology Biobricks' visualization.
BMC bioinformatics, 2017Co-Authors: Jiaoyun Yang, Haipeng Wang, Huitong Ding, Gil AlterovitzAbstract:Visualizing data by dimensionality reduction is an important strategy in Bioinformatics, which could help to discover hidden data properties and detect data quality issues, e.g. data noise, inappropriately labeled data, etc. As crowdsourcing-based synthetic biology databases face similar data quality issues, we propose to visualize Biobricks to tackle them. However, existing dimensionality reduction methods could not be directly applied on Biobricks datasets. Hereby, we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and Laplacian Eigenmaps. By extracting Biobricks from synthetic biology database Registry of Standard Biological Parts, six combinations of various types of Biobricks are tested. The visualization graphs illustrate discriminated Biobricks and inappropriately labeled Biobricks. Clustering algorithm K-means is adopted to quantify the reduction results. The average clustering accuracy for Isomap and Laplacian Eigenmaps are 0.857 and 0.844, respectively. Besides, Laplacian Eigenmaps is 5 times faster than Isomap, and its visualization graph is more concentrated to discriminate Biobricks. By combining normalized edit distance with Isomap and Laplacian Eigenmaps, synthetic biology biobircks are successfully visualized in two dimensional space. Various types of Biobricks could be discriminated and inappropriately labeled Biobricks could be determined, which could help to assess crowdsourcing-based synthetic biology databases’ quality, and make Biobricks selection.
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Additional file 1 of Nonlinear dimensionality reduction methods for synthetic biology Biobricksâ visualization
2017Co-Authors: Jiaoyun Yang, Haipeng Wang, Huitong Ding, Gil AlterovitzAbstract:This file contains more experiments on other types of Biobricks. Besides, classification validation for the dimensionality reduction results are also included. These results are illustrated in two figures and two tables in the file. Figure S1: Dimensionality reduction results for various combinations of Plasmid backbones, Promoters, Terminators, Translational units, Protein generators, Primers by applying Isomap algorithm. Figure S2: Dimensionality reduction results for various combinations of Plasmid backbones, Promoters, Terminators, Translational units, Protein generators, Primers by applying Laplacian Eigenmaps algorithm. Table S1: Clustering accuracy comparison of dimensionality reduction results in Figures S1 and S2. Table S2: Classification accuracy comparison of dimensionality reduction results by Isomap and Laplacian Eigenmaps. (PDF 123 kb
Drew Endy - One of the best experts on this subject based on the ideXlab platform.
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Measuring the activity of BioBrick promoters using an in vivo reference standard
Journal of Biological Engineering, 2009Co-Authors: Jason R Kelly, Adam J Rubin, Caroline M Ajo-franklin, John Cumbers, Michael J Czar, Kim De Mora, Aaron L Glieberman, Dileep D Monie, Joseph H Davis, Drew EndyAbstract:BackgroundThe engineering of many-component, synthetic biological systems is being made easier by the development of collections of reusable, standard biological parts. However, the complexity of biology makes it difficult to predict the extent to which such efforts will succeed. As a first practical example, the Registry of Standard Biological Parts started at MIT now maintains and distributes thousands of BioBrick™ standard biological parts. However, BioBrick parts are only standardized in terms of how individual parts are physically assembled into multi-component systems, and most parts remain uncharacterized. Standardized tools, techniques, and units of measurement are needed to facilitate the characterization and reuse of parts by independent researchers across many laboratories.ResultsWe found that the absolute activity of BioBrick promoters varies across experimental conditions and measurement instruments. We choose one promoter (BBa_J23101) to serve as an in vivo reference standard for promoter activity. We demonstrated that, by measuring the activity of promoters relative to BBa_J23101, we could reduce variation in reported promoter activity due to differences in test conditions and measurement instruments by ~50%. We defined a Relative Promoter Unit (RPU) in order to report promoter characterization data in compatible units and developed a measurement kit so that researchers might more easily adopt RPU as a standard unit for reporting promoter activity. We distributed a set of test promoters to multiple labs and found good agreement in the reported relative activities of promoters so measured. We also characterized the relative activities of a reference collection of BioBrick promoters in order to further support adoption of RPU-based measurement standards.ConclusionRelative activity measurements based on an in vivoreference standard enables improved measurement of promoter activity given variation in measurement conditions and instruments. These improvements are sufficient to begin to support the measurement of promoter activities across many laboratories. Additional in vivo reference standards for other types of biological functions would seem likely to have similar utility, and could thus improve research on the design, production, and reuse of standard biological parts.
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Measuring the activity of BioBrick promoters using an in vivo reference standard
Journal of biological engineering, 2009Co-Authors: Jason R Kelly, Adam J Rubin, Caroline M Ajo-franklin, John Cumbers, Michael J Czar, Kim De Mora, Aaron L Glieberman, Dileep D Monie, Joseph H Davis, Drew EndyAbstract:Background The engineering of many-component, synthetic biological systems is being made easier by the development of collections of reusable, standard biological parts. However, the complexity of biology makes it difficult to predict the extent to which such efforts will succeed. As a first practical example, the Registry of Standard Biological Parts started at MIT now maintains and distributes thousands of BioBrick™ standard biological parts. However, BioBrick parts are only standardized in terms of how individual parts are physically assembled into multi-component systems, and most parts remain uncharacterized. Standardized tools, techniques, and units of measurement are needed to facilitate the characterization and reuse of parts by independent researchers across many laboratories.
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Engineering BioBrick vectors from BioBrick parts
Journal of Biological Engineering, 2008Co-Authors: Reshma P Shetty, Drew Endy, Thomas F KnightAbstract:Background The underlying goal of synthetic biology is to make the process of engineering biological systems easier. Recent work has focused on defining and developing standard biological parts. The technical standard that has gained the most traction in the synthetic biology community is the BioBrick standard for physical composition of genetic parts. Parts that conform to the BioBrick assembly standard are BioBrick standard biological parts. To date, over 2,000 BioBrick parts have been contributed to, and are available from, the Registry of Standard Biological Parts. Results Here we extended the same advantages of BioBrick standard biological parts to the plasmid-based vectors that are used to provide and propagate BioBrick parts. We developed a process for engineering BioBrick vectors from BioBrick parts. We designed a new set of BioBrick parts that encode many useful vector functions. We combined the new parts to make a BioBrick base vector that facilitates BioBrick vector construction. We demonstrated the utility of the process by constructing seven new BioBrick vectors. We also successfully used the resulting vectors to assemble and propagate other BioBrick standard biological parts. Conclusion We extended the principles of part reuse and standardization to BioBrick vectors. As a result, myriad new BioBrick vectors can be readily produced from all existing and newly designed BioBrick parts. We invite the synthetic biology community to (1) use the process to make and share new BioBrick vectors; (2) expand the current collection of BioBrick vector parts; and (3) characterize and improve the available collection of BioBrick vector parts.
Herbert M. Sauro - One of the best experts on this subject based on the ideXlab platform.
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BioBrick™ assembly using the In-Fusion PCR Cloning Kit.
Methods in molecular biology (Clifton N.J.), 2013Co-Authors: Sean C. Sleight, Herbert M. SauroAbstract:Synthetic biologists assemble genetic circuits from standardized biological parts called Biobricks™. BioBrick™ examples include promoters, ribosome binding sites, DNA or RNA-coding sequences, and transcriptional terminators. Standard BioBrick™ assembly normally involves assembly of two Biobricks™ at a time using restriction enzymes and DNA ligase. Here we describe an alternative BioBrick™ assembly protocol that describes the assembly of two Biobricks™ using the In-Fusion PCR Cloning Kit. This protocol can also be adapted to use similar recombination-based assembly methods, such as SLIC and Gibson assembly.
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In-Fusion BioBrick assembly and re-engineering.
Nucleic acids research, 2010Co-Authors: Sean C. Sleight, Bryan A. Bartley, Jane A. Lieviant, Herbert M. SauroAbstract:Genetic circuits can be assembled from standardized biological parts called Biobricks. Examples of Biobricks include promoters, ribosome-binding sites, coding sequences and transcriptional terminators. Standard BioBrick assembly normally involves restriction enzyme digestion and ligation of two Biobricks at a time. The method described here is an alternative assembly strategy that allows for two or more PCR-amplified Biobricks to be quickly assembled and re-engineered using the Clontech In-Fusion PCR Cloning Kit. This method allows for a large number of parallel assemblies to be performed and is a flexible way to mix and match Biobricks. In-Fusion assembly can be semi-standardized by the use of simple primer design rules that minimize the time involved in planning assembly reactions. We describe the success rate and mutation rate of In-Fusion assembled genetic circuits using various homology and primer lengths. We also demonstrate the success and flexibility of this method with six specific examples of BioBrick assembly and re-engineering. These examples include assembly of two basic parts, part swapping, a deletion, an insertion, and three-way In-Fusion assemblies.
Sean C. Sleight - One of the best experts on this subject based on the ideXlab platform.
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assemble two Biobricks using the Clontech In-Fusion PCR Cloning Kit while maintaining
2016Co-Authors: Sean C. SleightAbstract:This Biobricks Foundation Request for Comments (BBF RFC) describes a method t
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BioBrick™ assembly using the In-Fusion PCR Cloning Kit.
Methods in molecular biology (Clifton N.J.), 2013Co-Authors: Sean C. Sleight, Herbert M. SauroAbstract:Synthetic biologists assemble genetic circuits from standardized biological parts called Biobricks™. BioBrick™ examples include promoters, ribosome binding sites, DNA or RNA-coding sequences, and transcriptional terminators. Standard BioBrick™ assembly normally involves assembly of two Biobricks™ at a time using restriction enzymes and DNA ligase. Here we describe an alternative BioBrick™ assembly protocol that describes the assembly of two Biobricks™ using the In-Fusion PCR Cloning Kit. This protocol can also be adapted to use similar recombination-based assembly methods, such as SLIC and Gibson assembly.
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In-Fusion BioBrick assembly and re-engineering.
Nucleic acids research, 2010Co-Authors: Sean C. Sleight, Bryan A. Bartley, Jane A. Lieviant, Herbert M. SauroAbstract:Genetic circuits can be assembled from standardized biological parts called Biobricks. Examples of Biobricks include promoters, ribosome-binding sites, coding sequences and transcriptional terminators. Standard BioBrick assembly normally involves restriction enzyme digestion and ligation of two Biobricks at a time. The method described here is an alternative assembly strategy that allows for two or more PCR-amplified Biobricks to be quickly assembled and re-engineered using the Clontech In-Fusion PCR Cloning Kit. This method allows for a large number of parallel assemblies to be performed and is a flexible way to mix and match Biobricks. In-Fusion assembly can be semi-standardized by the use of simple primer design rules that minimize the time involved in planning assembly reactions. We describe the success rate and mutation rate of In-Fusion assembled genetic circuits using various homology and primer lengths. We also demonstrate the success and flexibility of this method with six specific examples of BioBrick assembly and re-engineering. These examples include assembly of two basic parts, part swapping, a deletion, an insertion, and three-way In-Fusion assemblies.