1. Mammadova N., Keskin İ., 2013. Application of support vector machine to predict subclinical mastitis in dairy cattle. Scientific World Journal, (2013), 1-10.
2. Ser, G. Yeşilova, A.,Yılmaz A. 2013. Comparıng Covarıance Structures Using Different Optimization techniques in glm on some sexual behaviors of male lambs.TheJournal of Animal&PlantSciences, 23(6): 1583-1587.
3. Mikail N., Keskin İ., 2015. Subclinical mastitis prediction in dairy cattle application of fuzzy logic. Pak. J. Agri. Sci., Vol. 52(4), 1101-1107.
4. Mikail N., Keskin İ., 2015. Application of neural network and adaptive neuro-fuzzy inference system to predict subclinical mastitis in dairy cattle. Indian J. Anim. Res., 49 (5) 2015 : 671-679.
5. Ameen A.A., Mikail N., 2018. Live body weight prediction in hair goats by application of fuzzy logıc. Applied Ecology and Environmental Research, 16(6): 7563-7574.
6. Karipçin M.Z., Seyitoğlu G., Mikail N., 2018. Characterization of phytophthora capsici leonian resistance in some pepper genotypes by principal component analysis. Applied Ecology and Environmental Research, 16(5): 6885-6901.
7. Mikail N., Cue R., Bakır G., 2019. Most probable producing ability as a within-herd management and culling tool. The J. Anim. Plant Sci. 29(1): 48-57.
8. Pakyürek M., Aydın Y., Mikail N., 2019. Fuzzy logic applications in horticulture and a sample design for juice volume prediction in pomegranate (Punica Granatum L.). Applied Ecology and Environmental Research, 17(2): 2449-2460.