A case of a small-sized cavernous hemangioma in the right ventricle - an incidental finding.

A cardiac cavernous hemangioma is a rare, primary, benign tumor that is usually diagnosed in young or middle-aged patients. In this article, we report the case of a 71-year-old male patient whose doctors incidentally discovered a heart tumor on his transthoracic echocardiography. Triple-phase computed tomography (CT) (pre-contrast, arterial and portal venous) missed the lesion, and magnetic resonance imaging (MRI) revealed a small, oval tumor attached to the wall of the right ventricle.

De novo ChIP-seq analysis.

Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads to a reference genome. While often successful, they are not appropriate for cases where a reference genome is not available. Here we develop methods for de novo analysis of ChIP-seq data.

Integrating sequence, expression and interaction data to determine condition-specific miRNA regulation.

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. MiRNAs were shown to play an important role in development and disease, and accurately determining the networks regulated by these miRNAs in a specific condition is of great interest. Early work on miRNA target prediction has focused on using static sequence information.

MicroRNA regulation and its effects on cellular transcriptome in human immunodeficiency virus-1 (HIV-1) infected individuals with distinct viral load and CD4 cell counts.

Background: Disease progression in the absence of therapy varies significantly in HIV-1 infected individuals. Both viral and host cellular molecules are implicated; however, the exact role of these factors and/or the mechanism involved remains elusive. To understand how microRNAs (miRNAs), which are regulators of transcription and translation, influence host cellular gene expression (mRNA) during HIV-1 infection, we performed a comparative miRNA and mRNA microarray analysis using PBMCs obtained from infected individuals with distinct viral load and CD4 counts.

Probabilistic error correction for RNA sequencing.

Sequencing of RNAs (RNA-Seq) has revolutionized the field of transcriptomics, but the reads obtained often contain errors. Read error correction can have a large impact on our ability to accurately assemble transcripts. This is especially true for de novo transcriptome analysis, where a reference genome is not available.

Comparative expression profile of miRNA and mRNA in primary peripheral blood mononuclear cells infected with human immunodeficiency virus (HIV-1).

Host cells respond to exogenous infectious agents such as viruses, including HIV-1. Studies have evaluated the changes associated with virus infection at the transcriptional and translational levels of the cellular genes involved in specific pathways. While this approach is useful, in our view it provides only a partial view of genome-wide changes.

Cross-species queries of large gene expression databases.

Motivation: Expression databases, including the Gene Expression Omnibus and ArrayExpress, have experienced significant growth over the past decade and now hold hundreds of thousands of arrays from multiple species. Since most drugs are initially tested on model organisms, the ability to compare expression experiments across species may help identify pathways that are activated in a similar way in humans and other organisms. However, while several methods exist for finding co-expressed genes in the same species as a query gene, looking at co-expression of homologs or arbitrary genes in other species is challenging.

Cache-oblivious dynamic programming for bioinformatics.

We present efficient cache-oblivious algorithms for some well-studied string problems in bioinformatics including the longest common subsequence, global pairwise sequence alignment and three-way sequence alignment (or median), both with affine gap costs, and RNA secondary structure prediction with simple pseudoknots. For each of these problems, we present cache-oblivious algorithms that match the best-known time complexity, match or improve the best-known space complexity, and improve significantly over the cache-efficiency of earlier algorithms. We present experimental results which show that our cache-oblivious algorithms run faster than software and implementations based on previous best algorithms for these problems.

Pattern identification in biogeography.

Identifying common patterns among area cladograms that arise in historical biogeography is an important tool for biogeographical inference. We develop the first rigorous formalization of these pattern-identification problems. We develop metrics to compare area cladograms.