GEGE: Çizge Gömülümleriyle Gen Esaslılığını Tahmin Etme

Yıl 2022, Cilt: 10 Sayı: 3, 1567 - 1577, 31.07.2022

Halil İbrahim Kuru Yasin İlkağan Tepeli Öznur Taştan

https://doi.org/10.29130/dubited.1028387

Öz

İşlevi, bir hücrenin veya organizmanın hayatta kalabilmesi veya üreme başarısı için vazgeçilmez olan genler, esaslı genler olarak kabul edilir. Esaslı genleri esaslı olmayanlardan ayırt etmek, bir organizmanın minimum fonksiyonel gereksinimlerinin anlaşılabilmesi için genetikte kilit bir sorudur. Esaslı genler küme bilgisi, ilaç tasarlanmasında da çok önemlidir. Literatürdeki, bir protein-protein etkileşim ağındaki gen konumunun, gen esaslılığı ile ilişkili olduğunu göstermiştir. Burada, bir protein-protein etkileşimi (PPI) ağının düğüm yerleştirmelerinin gen gerekliliğini tahmin etmeye yardımcı olup olamayacağını soruyoruz. İnsan geninin esaslığını tahmin etme konusundaki sonuçlarımız, düğüm gömülümlerinin tek başına %88'e kadar AUC skoruna ulaşabileceğini göstermektedir. Bu skor, gen özelliklerini karakterize etmek için topolojik özellikleri kullanılan modellerin başarımından ve önceki çalışma sonuçlarından daha iyidir. Ayrıca, türler arası homoloji bilgisi ile birleştiğinde, bu performansın %89 AUC skoruna ulaştığını gösteriyoruz. Çalışmamız, PPI ağındaki bir proteinin düğüm gömülümlerinin, proteinlerin ağ bağlantı modellerini yakaladığını ve gen esaslılık tahminlerini geliştirdiğini gösteriyor.

Anahtar Kelimeler

Çizge gösterimleri, Düğüm gömülümleri, Gen esaslılığı, Ağ topolojik özellikleri, Protein-protein etkileşim ağı

Teşekkür

H. İ. Kuru İhsan Doğramacı Bilkent Üniversitesi Bilgisayar Mühendisliği Programının sağladığı bursa teşekkür eder. Y. i. Tepeli TUBITAK-BIDEB 2210-A bursuna teşekkür eder. Ö. T. BAGEP bursu için Bilim Akademisine teşekkür eder.

GEGE: Predicting Gene Essentiality with Graph Embeddings

Öz

A gene is considered essential if its function is indispensable for the viability or reproductive success of a cell or an organism. Distinguishing essential genes from non-essential ones is a fundamental question in genetics, and it is key to understanding the minimal set of functional requirements of an organism. Knowledge of the set of essential genes is also crucial in drug discovery. Several reports in the literature show that the gene location in a protein-protein interaction network is correlated with the target gene’s essentiality. Here, we ask whether the node embeddings of a protein-protein interaction (PPI) network can help predict gene essentiality. Our results on predicting human gene essentiality show that node embeddings alone can achieve up to 88% AUC score, which is better than using topological features to characterize gene properties and other previous work’s results. We also show that, when combined with homology information across species, this performance reaches 89% AUC. Our work shows that node embeddings of a protein in the PPI network capture the network connectivity patterns of the proteins and improve the gene essentiality predictions.

Anahtar Kelimeler

Graph representations, Node embeddings, Gene essentiality, Network topological features, Protein-protein interaction network

Kaynakça

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