Analysing the genetic diversity and population structure of five native Turkish cattle breeds using SNP data.

The conservation and sustainable utilization of cattle genetic resources necessitate a comprehensive understanding of their genetic diversity and population structure. This study provides an analysis of five native Turkish cattle breeds: Anatolian Black (ANB), Turkish Grey (TUR), Anatolian Southern Yellow (ASY), East Anatolian Red (EAR), and South Anatolian Red (SAN) using 50 K SNP data. These breeds were compared with three European breeds, Simmental (SIM), Holstein (HOL), and Jersey (JER), and three Asian Zebu breeds: Arabic Zebu (ZAR), Nelore (NEL), and Red Sindhi (RSI).

Two novel outlier detection approaches based on unsupervised possibilistic and fuzzy clustering.

Outliers are data points that significantly deviate from other data points in a data set because of different mechanisms or unusual processes. Outlier detection is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for data cleansing in data science. In this study, we propose two novel outlier detection approaches using the typicality degrees which are the partitioning result of unsupervised possibilistic clustering algorithms.