Evaluation of gene interaction and similarity in 17 different cancer pathways

Ertugrul Bursalıoğlu; Şaban Kalay

Makale detayları

Evaluation of gene interaction and similarity in 17 different cancer pathways

Yazarlar:

Ertugrul Bursalıoğlu | Şaban Kalay

Yayıncı:

Marmara University

Ana Başlıklar:

Pharmacology and Pharmaceutical Sciences (Other)

Dergi:

Journal of Research in Pharmacy Vol.29 Issue 2, pp.742-750

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341719

pISSN:

2630-6344

Anahtar kelimeler:

Özet:

 This study investigates similarities and gene interactions in 17 different cancer types using Kyoto Universitys KEGG cancer pathways. Using Python software and the Google Colab platform, gene similarities and interactions within cancer pathways were calculated through Jaccard similarity indices and interaction analyses. The results reveal important genes and pathways shared between cancer types, providing insights into common molecular mechanisms underlying cancer development and progression. These findings may contribute to the identification of potential therapeutic targets by understanding the biological processes shared between cancers. In comparisons between different cancer types, gene similarities ranged between 43 and 47 and pathway similarities ranged between 25 and 46. These results reveal that while some cancer types are genetically similar, they show differences in biochemical processes. In the gene interaction study among 17 different cancer pathways, the highest interaction rates were observed in colorectal cancer between entries 43-40 with activation, in pancreatic cancer between entries 113- 6 with activation, and in hepatocellular carcinoma between entries 122-224 with activation, showing nearly 100 interaction. On the other hand, the lowest interaction rates were found in colorectal cancer between entries 39-135 with missing interaction and in melanoma between entries 95-106 with missing interaction, showing 0 interaction.

 This study investigates similarities and gene interactions in 17 different cancer types using Kyoto Universitys KEGG cancer pathways. Using Python software and the Google Colab platform, gene similarities and interactions within cancer pathways were calculated through Jaccard similarity indices and interaction analyses. The results reveal important genes and pathways shared between cancer types, providing insights into common molecular mechanisms underlying cancer development and progression. These findings may contribute to the identification of potential therapeutic targets by understanding the biological processes shared between cancers. In comparisons between different cancer types, gene similarities ranged between 43 and 47 and pathway similarities ranged between 25 and 46. These results reveal that while some cancer types are genetically similar, they show differences in biochemical processes. In the gene interaction study among 17 different cancer pathways, the highest interaction rates were observed in colorectal cancer between entries 43-40 with activation, in pancreatic cancer between entries 113- 6 with activation, and in hepatocellular carcinoma between entries 122-224 with activation, showing nearly 100 interaction. On the other hand, the lowest interaction rates were found in colorectal cancer between entries 39-135 with missing interaction and in melanoma between entries 95-106 with missing interaction, showing 0 interaction.

 This study investigates similarities and gene interactions in 17 different cancer types using Kyoto Universitys KEGG cancer pathways. Using Python software and the Google Colab platform, gene similarities and interactions within cancer pathways were calculated through Jaccard similarity indices and interaction analyses. The results reveal important genes and pathways shared between cancer types, providing insights into common molecular mechanisms underlying cancer development and progression. These findings may contribute to the identification of potential therapeutic targets by understanding the biological processes shared between cancers. In comparisons between different cancer types, gene similarities ranged between 43 and 47 and pathway similarities ranged between 25 and 46. These results reveal that while some cancer types are genetically similar, they show differences in biochemical processes. In the gene interaction study among 17 different cancer pathways, the highest interaction rates were observed in colorectal cancer between entries 43-40 with activation, in pancreatic cancer between entries 113- 6 with activation, and in hepatocellular carcinoma between entries 122-224 with activation, showing nearly 100 interaction. On the other hand, the lowest interaction rates were found in colorectal cancer between entries 39-135 with missing interaction and in melanoma between entries 95-106 with missing interaction, showing 0 interaction.

 This study investigates similarities and gene interactions in 17 different cancer types using Kyoto Universitys KEGG cancer pathways. Using Python software and the Google Colab platform, gene similarities and interactions within cancer pathways were calculated through Jaccard similarity indices and interaction analyses. The results reveal important genes and pathways shared between cancer types, providing insights into common molecular mechanisms underlying cancer development and progression. These findings may contribute to the identification of potential therapeutic targets by understanding the biological processes shared between cancers. In comparisons between different cancer types, gene similarities ranged between 43 and 47 and pathway similarities ranged between 25 and 46. These results reveal that while some cancer types are genetically similar, they show differences in biochemical processes. In the gene interaction study among 17 different cancer pathways, the highest interaction rates were observed in colorectal cancer between entries 43-40 with activation, in pancreatic cancer between entries 113- 6 with activation, and in hepatocellular carcinoma between entries 122-224 with activation, showing nearly 100 interaction. On the other hand, the lowest interaction rates were found in colorectal cancer between entries 39-135 with missing interaction and in melanoma between entries 95-106 with missing interaction, showing 0 interaction.

Makale detayları

Evaluation of gene interaction and similarity in 17 different cancer pathways

Yazarlar:

Ertugrul Bursalıoğlu | Şaban Kalay

Yayıncı:

Marmara University

Ana Başlıklar:

Pharmacology and Pharmaceutical Sciences (Other)

Dergi:

Journal of Research in Pharmacy Vol.29 Issue 2, pp.742-750

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341719

pISSN:

2630-6344

Cancer pathways

Python

Jaccard similarity

gene interactions

Sayı

Makale detayları

Evaluation of gene interaction and similarity in 17 different cancer pathways

Yazarlar: Ertugrul Bursalıoğlu | Şaban Kalay

Yayıncı: Marmara University

Ana Başlıklar: Pharmacology and Pharmaceutical Sciences (Other)

Dergi: Journal of Research in Pharmacy Vol.29 Issue 2, pp.742-750

Belge Tipi: Makale

Yayın Tarihi: 8/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001341719

pISSN: 2630-6344

Cancer pathways

Python

Jaccard similarity

gene interactions

Sayı

Yazarlar:

Ertugrul Bursalıoğlu | Şaban Kalay

Yayıncı:

Marmara University

Ana Başlıklar:

Pharmacology and Pharmaceutical Sciences (Other)

Dergi:

Journal of Research in Pharmacy Vol.29 Issue 2, pp.742-750

Belge Tipi:

Makale

Yayın Tarihi:

8/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001341719

pISSN:

2630-6344