Iterative Integration of FE and FTC

Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed with rapid advances in MR data acquisition and image processing techniques. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for task-based and resting fMRI data. FMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing with no manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software-testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection comprising participants from 54 different studies in the OpenfMRI repository. We review the distinctive features of fMRIPrep in a qualitative comparison to other preprocessing workflows. We demonstrate that fMRIPrep achieves higher spatial accuracy as it introduces less uncontrolled spatial smoothness than commonly used preprocessing tools. FMRIPrep has the potential to transform fMRI research by equipping neuroscientists with a high-quality, robust, easy-to-use and transparent preprocessing workflow which can help ensure the validity of inference and the interpretability of their results.

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Iterative integration of TTEthernet network flows

International Journal of Critical Computer-Based Systems ◽

10.1504/ijccbs.2019.10026129 ◽

2019 ◽

Vol 9 (3) ◽

pp. 167

Author(s):

Sofiene Beji ◽

Sardaouna Hamadou ◽

Abdelouahed Gherbi ◽

John Mullins

Keyword(s):

Network Flows ◽

Iterative Integration

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Engineering the oleaginous yeast Yarrowia lipolytica for production of α-farnesene

Biotechnology for Biofuels ◽

10.1186/s13068-019-1636-z ◽

2019 ◽

Vol 12 (1) ◽

Cited By ~ 10

Author(s):

Yinghang Liu ◽

Xin Jiang ◽

Zhiyong Cui ◽

Zhaoxuan Wang ◽

Qingsheng Qi ◽

...

Keyword(s):

Yarrowia Lipolytica ◽

Mevalonate Pathway ◽

Lipid Production ◽

Economic Value ◽

Culture Conditions ◽

End Joining ◽

Expression Library ◽

Cofactor Specificity ◽

Non Homologous End Joining ◽

Iterative Integration

Abstract Background Yarrowia lipolytica, a non-traditional oil yeast, has been widely used as a platform for lipid production. However, the production of other chemicals such as terpenoids in engineered Y. lipolytica is still low. α-Farnesene, a sesquiterpene, can be used in medicine, bioenergy and other fields, and has very high economic value. Here, we used α-farnesene as an example to explore the potential of Y. lipolytica for terpenoid production. Results We constructed libraries of strains overexpressing mevalonate pathway and α-farnesene synthase genes by non-homologous end-joining (NHEJ) mediated integration into the Y. lipolytica chromosome. First, a mevalonate overproduction strain was selected by overexpressing relevant genes and changing the cofactor specificity. Based on this strain, the downstream α-farnesene synthesis pathway was overexpressed by iterative integration. Culture conditions were also optimized. A strain that produced 25.55 g/L α-farnesene was obtained. This is the highest terpenoid titer reported in Y. lipolytica. Conclusions Yarrowia lipolytica is a potentially valuable species for terpenoid production, and NHEJ-mediated modular integration is effective for expression library construction and screening of high-producer strains.

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