Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data

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Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data

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A fundamental fact in biology states that genes do not operate in isolation, and yet, methods that infer regulatory networks for single cell gene expression data have been slow to emerge. With single cell sequencing methods now becoming accessible, general network inference algorithms that were initially developed for data collected from bulk samples may not be suitable for single cells. |

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Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data

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Đang chuẩn bị liên kết để tải về tài liệu: Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data

Báo cáo khoa học: "Some Psychological Methods for Evaluating the Quality of Translations"

Báo cáo khoa học: "Methods and Practical Issues in Evaluating Alignment Techniques"

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Ebook Chemistry - Modern analytical chemistry: Part 1

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Topics in Current Chemistry Also Available Electronically

Researchingapplications of statistical methods in evaluating the quality of services of Vietnamese commercial banks - Illustrations through a specific research at the Joint Stock Commercial Bank of Investment and Development of Vietnam (BIDV)

Ebook Research design and methods - A process approach (8th edition): Part 1

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Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data