Gene regulatory networks and their applications: understanding biological and medical problems in terms of networks

نویسندگان

  • Frank Emmert-Streib
  • Matthias Dehmer
  • Benjamin Haibe-Kains
چکیده

In recent years gene regulatory networks (GRNs) have attracted a lot of interest and many methods have been introduced for their statistical inference from gene expression data. However, despite their popularity, GRNs are widely misunderstood. For this reason, we provide in this paper a general discussion and perspective of gene regulatory networks. Specifically, we discuss their meaning, the consistency among different network inference methods, ensemble methods, the assessment of GRNs, the estimated number of existing GRNs and their usage in different application domains. Furthermore, we discuss open questions and necessary steps in order to utilize gene regulatory networks in a clinical context and for personalized medicine.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Identification and prioritization genes related to Hypercholesterolemia QTLs using gene ontology and protein interaction networks

Gene identification represents the first step to a better understanding of the physiological role of the underlying protein and disease pathways, which in turn serves as a starting point for developing therapeutic interventions. Familial hypercholesterolemia is a hereditary metabolic disorder characterized by high low-density lipoprotein cholesterol levels. Hypercholesterolemia is a quantitativ...

متن کامل

Modeling gene regulatory networks: Classical models, optimal perturbation for identification of network

Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption.  On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications.  This is not an unrealistic goal since genes which are regulated by gene regulatory ...

متن کامل

Improving the Inference of Gene Expression Regulatory Networks with Data Aggregation Approach

Introduction: The major issue for the future of bioinformatics is the design of tools to determine the functions and all products of single-cell genes. This requires the integration of different biological disciplines as well as sophisticated mathematical and statistical tools. This study revealed that data mining techniques can be used to develop models for diagnosing high-risk or low-risk lif...

متن کامل

Improving the Inference of Gene Expression Regulatory Networks with Data Aggregation Approach

Introduction: The major issue for the future of bioinformatics is the design of tools to determine the functions and all products of single-cell genes. This requires the integration of different biological disciplines as well as sophisticated mathematical and statistical tools. This study revealed that data mining techniques can be used to develop models for diagnosing high-risk or low-risk lif...

متن کامل

Comparison of MLP NN Approach with PCA and ICA for Extraction of Hidden Regulatory Signals in Biological Networks

The biologists now face with the masses of high dimensional datasets generated from various high-throughput technologies, which are outputs of complex inter-connected biological networks at different levels driven by a number of hidden regulatory signals. So far, many computational and statistical methods such as PCA and ICA have been employed for computing low-dimensional or hidden represe...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره 2  شماره 

صفحات  -

تاریخ انتشار 2014