Evaluation of Performance of Machine Learning Algorithms Using Orange Data Analysis Tool in Protein Function Estimation Process

Ceren Akman Yaman; Volkan Altuntaş

Makale detayları

Evaluation of Performance of Machine Learning Algorithms Using Orange Data Analysis Tool in Protein Function Estimation Process

Yazarlar:

Ceren Akman Yaman | Volkan Altuntaş

Yayıncı:

Duzce University

Ana Başlıklar:

Mühendislik

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1334-1345

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001323923

pISSN:

2148-2446

Anahtar kelimeler:

Özet:

 The human body has been an intriguing mechanism in terms of functioning in all processes from the first day to the present. The vital cycle has continued and continues with the cells it contains and the molecules and processes that these cells contain. It has been concluded that understanding the functioning of molecules has an important effect on the analysis of vital activities in order to continue this vital cycle. When the studies carried out within the scope of this study were examined, it was concluded that the functioning of molecules, which have a complex structure for the human body, is of great importance. Thus, by considering the complex protein molecule, which is of great importance in this study, it is possible to perform the function estimation process in terms of biological process, molecular function and cellular component, and for this, data visualization and data visualization of k-nearest neighbor, neural network and random forest methods. The development of the models was provided by the Orange editor, which can be used in the analysis phase, and the performance evaluation was made. As a result of the evaluations, it was determined that the k-nearest neighbor model achieved at least 88 success on the data sets used.

 The human body has been an intriguing mechanism in terms of functioning in all processes from the first day to the present. The vital cycle has continued and continues with the cells it contains and the molecules and processes that these cells contain. It has been concluded that understanding the functioning of molecules has an important effect on the analysis of vital activities in order to continue this vital cycle. When the studies carried out within the scope of this study were examined, it was concluded that the functioning of molecules, which have a complex structure for the human body, is of great importance. Thus, by considering the complex protein molecule, which is of great importance in this study, it is possible to perform the function estimation process in terms of biological process, molecular function and cellular component, and for this, data visualization and data visualization of k-nearest neighbor, neural network and random forest methods. The development of the models was provided by the Orange editor, which can be used in the analysis phase, and the performance evaluation was made. As a result of the evaluations, it was determined that the k-nearest neighbor model achieved at least 88 success on the data sets used.

 The human body has been an intriguing mechanism in terms of functioning in all processes from the first day to the present. The vital cycle has continued and continues with the cells it contains and the molecules and processes that these cells contain. It has been concluded that understanding the functioning of molecules has an important effect on the analysis of vital activities in order to continue this vital cycle. When the studies carried out within the scope of this study were examined, it was concluded that the functioning of molecules, which have a complex structure for the human body, is of great importance. Thus, by considering the complex protein molecule, which is of great importance in this study, it is possible to perform the function estimation process in terms of biological process, molecular function and cellular component, and for this, data visualization and data visualization of k-nearest neighbor, neural network and random forest methods. The development of the models was provided by the Orange editor, which can be used in the analysis phase, and the performance evaluation was made. As a result of the evaluations, it was determined that the k-nearest neighbor model achieved at least 88 success on the data sets used.

 İnsan vücudu ilk günden bugüne kadar olan bütün süreçlerde işleyiş açısından merak uyandıran bir mekanizma olmuştur. İçerisinde barındırdığı hücrelerle bu hücrelerin kendi içlerinde barındırdıkları moleküllerle ve işleyişlerle yaşamsal döngü devam etmiştir ve devam etmektedir. Bu yaşamsal döngünün devam etmesi için moleküllerin işleyiş şekillerinin anlaşılmasının yaşamsal faaliyetlerin çözümlenmesinde önemli etkisi olduğu kanısına varılmıştır. Bu çalışma kapsamında yapılan çalışmalar incelendiğinde insan vücudu için karmaşık bir yapıya sahip olan moleküllerin işleyişinin büyük bir öneme sahip olduğu kararına varılmıştır. Böylelikle bu çalışma da büyük bir öneme sahip olan karmaşık yapılı protein molekülü ele alınarak biyoloji tarafından bakıldığında biyolojik süreç, moleküler işlev ve hücresel bileşen açısından fonksiyon tahmin işleminin gerçekleştirilebilmesi ve bunun için k- en yakın komşuluk, sinir ağı ve rastgele orman yöntemlerinin veri görselleştirme ve veri analiz aşamasında kullanılabilen Orange editörü vasıtasıyla modellerin geliştirilmesi sağlanmış olup performans değerlendirilmesi yapılmıştır. Yapılan değerlendirmeler sonucunda k-en yakın komşuluk modelinin kullanılan veri setleri üzerinde en az 88 üzerinde başarı sağladığı tespit edilmiştir.

Makale detayları

Evaluation of Performance of Machine Learning Algorithms Using Orange Data Analysis Tool in Protein Function Estimation Process

Yazarlar:

Ceren Akman Yaman | Volkan Altuntaş

Yayıncı:

Duzce University

Ana Başlıklar:

Mühendislik

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1334-1345

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001323923

pISSN:

2148-2446

Bioinformatics

Protein function

Neural network

Random forest

K-Nearest neighborhoodBiyoinformatik

Protein Fonksiyonu

Sinir Ağı

Rastgele Orman

K-En Yakın Komşuluk

Sayı

Makale detayları

Yazarlar: Ceren Akman Yaman | Volkan Altuntaş

Yayıncı: Duzce University

Ana Başlıklar: Mühendislik

Dergi: Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1334-1345

Belge Tipi: Makale

Yayın Tarihi: 7/2024

Belge Dili: Türkçe

Document ID (Org No.): 2001323923

pISSN: 2148-2446

Sayı

Yazarlar:

Ceren Akman Yaman | Volkan Altuntaş

Yayıncı:

Duzce University

Ana Başlıklar:

Mühendislik

Dergi:

Düzce Üniversitesi Bilim ve Teknoloji Dergisi Vol.12 Issue 3, pp.1334-1345

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

Türkçe

Document ID (Org No.):

2001323923

pISSN:

2148-2446