Yasin Tepeli

About Yasin Tepeli

Yasin Tepeli, With an exceptional h-index of 3 and a recent h-index of 3 (since 2020), a distinguished researcher at Technische Universiteit Delft, specializes in the field of Machine Learning in Health, Graphs.

His recent articles reflect a diverse array of research interests and contributions to the field:

ELISL: early–late integrated synthetic lethality prediction in cancer

Overcoming selection bias in synthetic lethality prediction

GEGE: predicting gene essentiality with graph embeddings

PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering

A pathway graph kernel based multi-omics approach for patient clustering

Yasin Tepeli Information

University

Position

___

Citations(all)

32

Citations(since 2020)

32

Cited By

8

hIndex(all)

3

hIndex(since 2020)

3

i10Index(all)

1

i10Index(since 2020)

1

Email

University Profile Page

Google Scholar

Yasin Tepeli Skills & Research Interests

Machine Learning in Health

Graphs

Top articles of Yasin Tepeli

Title

Journal

Author(s)

Publication Date

ELISL: early–late integrated synthetic lethality prediction in cancer

Bioinformatics

Yasin I Tepeli

Colm Seale

Joana P Gonçalves

2024/1/1

Overcoming selection bias in synthetic lethality prediction

Bioinformatics

Colm Seale

Yasin Tepeli

Joana P Gonçalves

2022/9/15

GEGE: predicting gene essentiality with graph embeddings

Düzce Üniversitesi Bilim ve Teknoloji Dergisi

Halil İbrahim Kuru

Yasin İlkağan Tepeli

Öznur Taştan

2022/7/31

PAMOGK: a pathway graph kernel-based multiomics approach for patient clustering

Bioinformatics

Yasin Ilkagan Tepeli

Ali Burak Ünal

Furkan Mustafa Akdemir

Oznur Tastan

2020/11/1

A pathway graph kernel based multi-omics approach for patient clustering

Yasin İlkağan Tepeli

2020/8/18

See List of Professors in Yasin Tepeli University(Technische Universiteit Delft)

Co-Authors

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