[Luận văn tiếng Anh] Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases
- Seiten
- 11
- Định dạng
- DOCX
- Dung lượng
- 3.6 MB
- Ngôn ngữ
- VI · Tiếng Việt
- Aufrufe
- 776
- Kommentare
- 0
- Lượt tải
- 0
Vorschau wird generiert...
- Dokumentenname
- [Luận văn tiếng Anh] Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases
- Inhaltsverzeichnis
- Dieses Dokument hat kein eindeutiges Inhaltsverzeichnis.
- Seiten
- 11 Seiten
- Hochgeladen von
- ThiNganHang
Eine detaillierte Zusammenfassung wird generiert. Bitte schauen Sie in ein paar Minuten noch einmal vorbei.
Beschreibung
Trích nội dung tài liệu
MINISTRY OF EDUCATION AND TRAINING HANOI NATIONAL UNIVERSITY OF EDUCATION NGUYEN VAN TINH LINK PREDICTION IN HETEROGENEOUS INFORMATION NETWORKS AND ITS APPLICATIONS IN PREDICTING ASSOCIATIONS BETWEEN NON-CODING RNAS AND DISEASES DOCTORAL DISSERTATION IN COMPUTER SCIENCE HANOI-2023 MINISTRY OF EDUCATION AND TRAINING HANOI NATIONAL UNIVERSITY OF EDUCATION NGUYEN VAN TINH LINK PREDICTION IN HETEROGENEOUS INFORMATION NETWORKS AND ITS APPLICATIONS IN PREDICTING ASSOCIATIONS BETWEEN NON-CODING RNAS AND DISEASES Major: Computer Science Code: 9480101 DOCTORAL DISSERTATION IN COMPUTER SCIENCE SUPERVISORS 1. Assoc. Prof. Dr. TRAN DANG HUNG 2. Dr. LE THI TU KIEN Hanoi-2023 i AUTHORSHIP'S DECLARATION I, NGUYEN VAN TINH, affirm that the dissertation entitled “Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases” has been completed by myself under the supervision of Assoc.Prof.Dr. Tran Dang Hung and Dr. Le Thi Tu Kien. I assure some points as follows: - This dissertation was done in the Ph.D. research time at Hanoi National University of Education. - This work has not been submitted for any other degrees or qualifications at Hanoi National University of Education or any other institutions. - Appropriate acknowledgment has been given in the thesis where references have been made to the other published works. - The submitted thesis is my own, except the work in the collaboration has been included. The collaborative contributions have been indicated. Hanoi, 2023 Ph.D. Student SUPERVISORS: 1. Assoc. Prof. Dr. TRAN DANG HUNG 2. Dr. LE THI TU KIEN
Häufig gestellte Fragen
Wie lade ich dieses Dokument herunter?
Das Dokument „[Luận văn tiếng Anh] Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases“ kostet 71.000đ. Laden Sie Ihr Guthaben über PayOS auf, klicken Sie dann auf Herunterladen, um die Originaldatei zu kaufen und zu speichern.
Wie viele Seiten hat dieses Dokument?
Das Dokument hat 11 Seiten. Sie können es vor dem Herunterladen online in der Vorschau ansehen.
Kann ich vor dem Herunterladen eine Vorschau ansehen?
Ja. Sie können sich dieses Dokument direkt auf dieser Seite im Online-Reader ansehen (die ersten paar Seiten) und dann entscheiden, ob Sie es herunterladen möchten.
[Luận văn tiếng Anh] Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases
Vorschau wird generiert...
Trích nội dung tài liệu
MINISTRY OF EDUCATION AND TRAINING HANOI NATIONAL UNIVERSITY OF EDUCATION NGUYEN VAN TINH LINK PREDICTION IN HETEROGENEOUS INFORMATION NETWORKS AND ITS APPLICATIONS IN PREDICTING ASSOCIATIONS BETWEEN NON-CODING RNAS AND DISEASES DOCTORAL DISSERTATION IN COMPUTER SCIENCE HANOI-2023 MINISTRY OF EDUCATION AND TRAINING HANOI NATIONAL UNIVERSITY OF EDUCATION NGUYEN VAN TINH LINK PREDICTION IN HETEROGENEOUS INFORMATION NETWORKS AND ITS APPLICATIONS IN PREDICTING ASSOCIATIONS BETWEEN NON-CODING RNAS AND DISEASES Major: Computer Science Code: 9480101 DOCTORAL DISSERTATION IN COMPUTER SCIENCE SUPERVISORS 1. Assoc. Prof. Dr. TRAN DANG HUNG 2. Dr. LE THI TU KIEN Hanoi-2023 i AUTHORSHIP'S DECLARATION I, NGUYEN VAN TINH, affirm that the dissertation entitled “Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases” has been completed by myself under the supervision of Assoc.Prof.Dr. Tran Dang Hung and Dr. Le Thi Tu Kien. I assure some points as follows: - This dissertation was done in the Ph.D. research time at Hanoi National University of Education. - This work has not been submitted for any other degrees or qualifications at Hanoi National University of Education or any other institutions. - Appropriate acknowledgment has been given in the thesis where references have been made to the other published works. - The submitted thesis is my own, except the work in the collaboration has been included. The collaborative contributions have been indicated. Hanoi, 2023 Ph.D. Student SUPERVISORS: 1. Assoc. Prof. Dr. TRAN DANG HUNG 2. Dr. LE THI TU KIEN
- Dokumentenname
- [Luận văn tiếng Anh] Link prediction in heterogeneous information networks and its applications in predicting associations between non-coding RNAs and diseases
- Inhaltsverzeichnis
- Dieses Dokument hat kein eindeutiges Inhaltsverzeichnis.
- Seiten
- 11 Seiten
- Hochgeladen von
- ThiNganHang
Eine detaillierte Zusammenfassung wird generiert. Bitte schauen Sie in ein paar Minuten noch einmal vorbei.
Kommentare (0)
Noch keine Kommentare. Seien Sie der Erste!
Tiểu luận - Phân tích Lý thuyết bàn tay vô hình của A.Smith và những bài học cho Việt Nam
[Báo cáo thực tập] Công ty Cổ Phần Tập Đoàn Sunhouse
Bài tiểu luận 9,5 điểm - Chuyên Đề Khởi Sự kinh doanh về ý tưởng khởi nghiệp
[Khóa luận] Hoàn thiện công tác quản trị rủi ro tại Công ty TNHH Cơ khí xây dựng VDC
[Đề án] Xuất khẩu vải thiều Bắc Giang vào thị trường Mỹ
Tiểu luận - Kinh tế phát triển - Phân tích nhận định "Việt Nam đã kiên định chọn hướng phát triển lấy con người làm trọng tâm ..."
Đề cương - Luật vận tải
600 Câu trắc nghiệm Tư tưởng Hồ Chí Minh
Tài liệu ôn tập Nguyên lý kế toán
Bài tập Xác suất thống kê đại học - có lời giải

Kommentare (0)
Noch keine Kommentare. Seien Sie der Erste!