Computational RNA Structure Prediction

نویسندگان

  • Emidio Capriotti
  • Marc A. Marti-Renom
چکیده

The view of RNA as simple information transfer molecule has been continuously challenged since the discovery of ribozymes, a class of RNA molecules with enzyme-like function. Moreover, the recent discovery of tiny RNA molecules such as RNAs and small interfering RNA, is transforming our thinking about how gene expression is regulated. Thus, RNA molecules are now known to carry a large repertory of biological functions within cells including information transfer, enzymatic catalysis and regulation of cellular processes. Similar to proteins, functional RNA molecules fold into their native three-dimensional (3D) conformation, which is essential for performing their biological activity. Despite advances in understanding the folding and unfolding of RNA, our knowledge of the atomic mechanism by which RNA molecules adopt their biological active structure is still limited. In this review, we outline the general principles that govern RNA structure and describe the databases and algorithms for analyzing and predicting RNA secondary and tertiary structure. Finally, we assess the impact of the current coverage of the RNA structural space on comparative modeling RNA structures.

برای دانلود 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

PreRkTAG: Prediction of RNA Knotted Structures Using Tree Adjoining Grammars

Background: RNA molecules play many important regulatory, catalytic and structural <span style="font-variant: normal; font-style: norma...

متن کامل

Consensus Folding of Unaligned RNA Sequences Revisited

As one of the earliest problems in computational biology, RNA secondary structure prediction (sometimes referred to as "RNA folding") problem has attracted attention again, thanks to the recent discoveries of many novel non-coding RNA molecules. The two common approaches to this problem are de novo prediction of RNA secondary structure based on energy minimization and the consensus folding appr...

متن کامل

Predicting pseudoknotted structures across two RNA sequences

MOTIVATION Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accura...

متن کامل

RNA structure prediction: progress and perspective

Many recent exciting discoveries have revealed the versatility of RNAs and their importance in a variety of cellular functions which are strongly coupled to RNA structures. To understand the functions of RNAs, some structure prediction models have been developed in recent years. In this review, the progress in computational models for RNA structure prediction is introduced and the distinguishin...

متن کامل

CyloFold: secondary structure prediction including pseudoknots

UNLABELLED Computational RNA secondary structure prediction approaches differ by the way RNA pseudoknot interactions are handled. For reasons of computational efficiency, most approaches only allow a limited class of pseudoknot interactions or are not considering them at all. Here we present a computational method for RNA secondary structure prediction that is not restricted in terms of pseudok...

متن کامل

Approximation Scheme for RNA Structure Prediction Based on Base Pair Stacking

Pseudoknotted RNA secondary structure prediction is an important problem in computational biology. Existing polynomial time algorithms have no performance guarantee or can handle only limited types of pseudoknots. In this paper for the general problem of pseudoknotted RNA secondary structure prediction, a polynomial time approximation scheme is presented to predict pseudoknotted RNA secondary s...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007