An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data
المؤلفون المشاركون
Altaf-Ul-Amin, Md.
Katsuragi, Tetsuo
Ono, Naoaki
Kanaya, Shigehiko
Sato, Tetsuo
المصدر
العدد
المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2014-03-31
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
This work presents a novel approach to predict functional relations between genes using gene expression data.
Genes may have various types of relations between them, for example, regulatory relations, or they may be concerned with the same protein complex or metabolic/signaling pathways and obviously gene expression data should contain some clues to such relations.
The present approach first digitizes the log-ratio type gene expression data of S.
cerevisiae to a matrix consisting of 1, 0, and −1 indicating highly expressed, no major change, and highly suppressed conditions for genes, respectively.
For each gene pair, a probability density mass function table is constructed indicating nine joint probabilities.
Then gene pairs were selected based on linear and probabilistic relation between their profiles indicated by the sum of probability density masses in selected points.
The selected gene pairs share many Gene Ontology terms.
Furthermore a network is constructed by selecting a large number of gene pairs based on FDR analysis and the clustering of the network generates many modules rich with similar function genes.
Also, the promoters of the gene sets in many modules are rich with binding sites of known transcription factors indicating the effectiveness of the proposed approach in predicting regulatory relations.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Altaf-Ul-Amin, Md.& Katsuragi, Tetsuo& Sato, Tetsuo& Ono, Naoaki& Kanaya, Shigehiko. 2014. An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data. BioMed Research International،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-450165
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Altaf-Ul-Amin, Md.…[et al.]. An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data. BioMed Research International No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-450165
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Altaf-Ul-Amin, Md.& Katsuragi, Tetsuo& Sato, Tetsuo& Ono, Naoaki& Kanaya, Shigehiko. An Unsupervised Approach to Predict Functional Relations between Genes Based on Expression Data. BioMed Research International. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-450165
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-450165
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر