IEEE/ACM Transactions on Computational Biology and Bioinformatics

Extracting information about the structure of biological tissue from static image data is a complex task requiring computationally intensive operations. Here, we present how multicore CPUs and GPUs have been utilized to extract information about the ...

Space is a very important aspect in the simulation of biochemical systems; recently, the need for simulation algorithms able to cope with space is becoming more and more compelling. Complex and detailed models of biochemical systems need to deal with ...

Regulation of gene expression is a carefully regulated phenomenon in the cell. "Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). ...

Markov clustering (MCL) is becoming a key algorithm within bioinformatics for determining clusters in networks. However, with increasing vast amount of data on biological networks, performance and scalability issues are becoming a critical limiting ...

An important problem in current computational systems biology is to analyze models of biological systems dynamics under parameter uncertainty. This paper presents a novel algorithm for parameter synthesis based on parallel model checking. The algorithm ...

In the biological domain, clustering is based on the assumption that genes or metabolites involved in a common biological process are coexpressed/coaccumulated under the control of the same regulatory network. Thus, a detailed inspection of the grouped ...

Several approaches have been presented in the literature to cluster Protein-Protein Interaction (PPI) networks. They can be grouped in two main categories: those allowing a protein to participate in different clusters and those generating only ...

Filtering of Protein Secondary Structure Prediction (PSSP) aims to provide physicochemically realistic results, while it usually improves the predictive performance. We performed a comparative study on this challenging problem, utilizing both machine ...

The functional annotation of proteins is one of the most important tasks in the post-genomic era. Although many computational approaches have been developed in recent years to predict protein function, most of these traditional algorithms do not take ...

Most of the conventional feature selection algorithms have a drawback whereby a weakly ranked gene that could perform well in terms of classification accuracy with an appropriate subset of genes will be left out of the selection. Considering this ...

Ab initio protein structure prediction methods first generate large sets of structural conformations as candidates (called decoys), and then select the most representative decoys through clustering techniques. Classical clustering methods are ...

Detecting members of known noncoding RNA (ncRNA) families in genomic DNA is an important part of sequence annotation. However, the most widely used tool for modeling ncRNA families, the covariance model (CM), incurs a high-computational cost when used ...

The availability of a great range of prior biological knowledge about the roles and functions of genes and gene-gene interactions allows us to simplify the analysis of gene expression data to make it more robust, compact, and interpretable. Here, we ...

Predicting the secondary structure of proteins is still a typical step in several bioinformatic tasks, in particular, for tertiary structure prediction. Notwithstanding the impressive results obtained so far, mostly due to the advent of sequence ...

The problem of identifying the proteins in a complex mixture using tandem mass spectrometry can be framed as an inference problem on a graph that connects peptides to proteins. Several existing protein identification methods make use of statistical ...

A new manifold learning method, called parameter-free semi-supervised local Fisher discriminant analysis (pSELF), is proposed to map the gene expression data into a low-dimensional space for tumor classification. Motivated by the fact that semi-...

We consider novel phylogenetic models with rate matrices that arise via the embedding of a progenitor model on a small number of character states, into a target model on a larger number of character states. Adapting representation-theoretic results from ...

Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) is useful in small-scale basic research studies of complex genetic diseases that are associated with single nucleotide polymorphism (SNP). Designing a feasible primer pair is ...

Biological cell cryopreservation permits storage of specimens for future use. Stem cell cryostorage in particular is fast becoming a broadly spread practice due to their potential for use in regenerative medicine. For the optimal cryopreservation ...

Detecting protein complexes from protein interaction networks is one major task in the postgenome era. Previous developed computational algorithms identifying complexes mainly focus on graph partition or dense region finding. Most of these traditional ...

Bistability/Multistability has been found in many biological systems including genetic memory circuits. Proper characterization of system stability helps to understand biological functions and has potential applications in fields such as synthetic ...

In vitro assembly of intermediate filaments from tetrameric vimentin consists of a very rapid phase of tetramers laterally associating into unit-length filaments and a slow phase of filament elongation. We focus in this paper on a systematic ...

Enormous data collection efforts and improvements in technology have made large genome-wide association studies a promising approach for better understanding the genetics of common diseases. Still, the knowledge gained from these studies may be extended ...

Important achievements in traditional biology have deepened the knowledge about living systems leading to an extensive identification of parts-list of the cell as well as of the interactions among biochemical species responsible for cell's regulation. ...

The scope and effectiveness of Rank Aggregation (RA) have already been established in contemporary bioinformatics research. Rank aggregation helps in meta-analysis of putative results collected from different analytic or experimental sources. For ...

"Signal” alignments play critical roles in many clinical setting. This is the case of mass spectrometry (MS) data, an important component of many types of proteomic analysis. A central problem occurs when one needs to integrate (MS) data produced by ...

We comment on the flexibility profiles calculated by Zeng et al., and show that these profiles do not represent the local flexibility of the DNA molecule. If one takes into account the physics of elasticity, the averaged flexibility profile show an ...