CLASSIFYING PROTEIN S-FARNESYLATION SITES WITH SUPPORT VECTOR MACHINE AND DECISION TREE

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Tác giả: Văn Núi Nguyễn, Thị Xuân Trần

Ngôn ngữ: Vie

Ký hiệu phân loại:

Thông tin xuất bản: Tạp chí Khoa học và Công nghệ Đại học Thái Nguyên, 2019

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 414432

Thêm vào giỏ Liên kết toàn văn

Protein Prenylation sự bổ sung của các phân tử kháng nước tới một protein hoặc một hợp chất hóa học. Nó là một quá trình biến đổi hậu dịch mã (PTM Post Translational Modification) đóng vai trò rất quan trọng, ảnh hưởng đến nhiều quá trình phân tử cũng như ảnh hưởng đến nhiều chức năng tế bào khác. Protein S-Farnesyl Cysteine Prenylation là một trường hợp đặc biệt của Prenylation liên quan đến sự dịch chuyển của một phân nửa (moiety) farnesyl tới một cysteine tế bào chất tại hoặc gần khu vực đầu cuối-C (C-turminus) của protein mục tiêu. Những phát hiện gần đây cho thấy vai trò rất quan trọng của S-Farnesyl Cysteine Prenylation (SFCP) ảnh hưởng đến nhiều quá trình sinh học cũng như có liên quan đến rất nhiều căn bệnh phổ biến hiện nay. Cho đến nay, có khá nhiều nghiên cứu về SFCP, đồng thời một vài công cụ tính toán cũng đã được đề xuất cho việc phân lớp, dự đoán vị trí SFCP. Tuy nhiên, hầu hết các nghiên cứu và công cụ dự đoán này hoặc chưa đáp ứng được các yêu cầu về kiến thức sâu rộng liên quan, hoặc hiệu năng dự đoán chưa đáp ứng được kỳ vọng. Vì vậy, trong nghiên cứu này chúng tôi đề xuất cách tiếp cận phân lớp vị trí protein SFCP trên cơ sở kết hợp sử dụng các phương pháp học máy và cây quyết định. Nhiều đặc trưng được tiến hành thử nghiệm để xây dựng mô hình dự đoán có hiệu năng tốt nhất. Kết quả cho thấy mô hình mà chúng tôi đề xuất có tính khả thi cao trong việc dự đoán vị trí SFCP. Điều này có thể sẽ là gợi ý về một hướng tiếp cận có thể giúp ích hữu hiệu cho các nhà nghiên cứu liên quan đến việc SFCP., Tóm tắt tiếng anh, Protein prenylation is the addition of hydrophobic molecules to a protein or a chemical compound. It is a post-translational modification that plays very important roles affecting to many cellular processes as well as many other cellular functions. Protein S-farnesyl cysteine prenylation is a specific kind of prenylation related to the transfer of a farnesyl moiety to a cytoplasmic cysteine at or near the C-terminus of the target protein. Recent findings have exhibited the very important roles of S-Farnesyl Cysteine Prenylation (SFCP) that affect to many biological processes as well as have involed in many current common diseases. So far, there has been some researches on SFCP, and several computational tools have been proposed for the classification, prediction of SFCP sites. However, almost of them have not met our demand on related extensive knowlegde, or the predictive performance has not met the requirements. Therefore, in this work, we are motivated to propose an approach to classify protein SFCP based on the incorporation of support vector machine and decision tree. Various features have been investigated to generate the optimal model that has highest predictive performance. The obtained results have demonstrated its ability and feasiblity in the classification of SFCP sites. This could be a suggestion on an approach that can useful for researchers regarding to SFCP.

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