Junilda Spirollari's research works | New Jersey Institute of Technology, New Jersey (NJIT) and other places

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RNA Classification and Structure Prediction: Algorithms and Case Studies

Chapter

Dec 2013

This chapter presents two case studies related to RNA data analysis. The first case study focuses on classification of microRNA precursors (also known as pre-miRNAs). The second case study focuses on prediction of RNA secondary structures, including pseudoknots. Pseudoknots are important RNA tertiary motifs. The authors describe in detail the probl...

Using folding ensemble and stem probability maximization methods to predict RNA H-type pseudoknots

Article

Dec 2012

We present in this paper an ab initio method, named KnotFold, for RNA H-type pseudoknot prediction. Our method employs an ensemble of RNA folding tools and a filtering heuristic to generate a set of pseudoknot-free stems, and then predicts pseudoknots by utilizing a search technique with a pseudo-probability scoring scheme. Experimental results sho...

Consensus Structure Prediction for RNA Alignments

Chapter

Sep 2009

RNA secondary structure prediction has been studied for quite awhile. Many minimum free energy (MFE) methods have been developed for predicting the secondary structures of single RNA sequences, such as mfold [1], RNAfold [2], MPGAfold [3], as well as recent tools presented in the literature [4, 5]. However, the accuracy of predicted structures is f...

Predicting Consensus Structures for RNA Alignments Via Pseudo-Energy Minimization

Article

Full-text available

Jun 2009

Thermodynamic processes with free energy parameters are often used in algorithms that solve the free energy minimization problem to predict secondary structures of single RNA sequences. While results from these algorithms are promising, an observation is that single sequence-based methods have moderate accuracy and more information is needed to imp...

Bioinformatic Databases

Chapter

Dec 2007

Biological database research encompasses many topics, such as biological data management, curation, quality, integration, and mining. Biological databases can be classified in many different ways, from the topic they cover, to how heavily annotated they are or which annotation method they employ, to how heavily annotated they are or which annotatio...

A New Algorithm for RNA Secondary Structure Prediction.

Conference Paper