Stock market reactions to COVID-19 lockdown: A global analysis.

The COVID-19 pandemic has caused dramatic changes in the way people around the globe live, and has had a profound negative impact on the global economy. Much of this negative impact did not result from the disease itself, but from the lockdown restrictions imposed to contain the spread of the virus. We investigate how national stock market indices reacted to the news of national lockdown restrictions in the period from January to May 2020.

A novel genomic alteration of LSAMP associates with aggressive prostate cancer in African American men.

Evaluation of cancer genomes in global context is of great interest in light of changing ethnic distribution of the world population. We focused our study on men of African ancestry because of their disproportionately higher rate of prostate cancer (CaP) incidence and mortality. We present a systematic whole genome analyses, revealing alterations that differentiate African American (AA) and Caucasian American (CA) CaP genomes.

Detecting and visualizing gene fusions.

In recent years, gene fusions have gained significant recognition as biomarkers. They can assist treatment decisions, are seldom found in normal tissue and are detectable through Next-generation sequencing (NGS) of the transcriptome (RNA-seq). To transform the data provided by the sequencer into robust gene fusion detection several analysis steps are needed.

Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies.

Next-generation sequencing is excellently suited to evaluate the abundance of mRNAs to study gene expression. Here we compare two alternative technologies, cap analysis of gene expression (CAGE) and serial analysis of gene expression (SAGE), for the same RNA samples. Along with quantifying gene expression levels, CAGE can be used to identify tissue-specific transcription start sites, while SAGE monitors 3'-end usage.

A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome.

The functional complexity of the human transcriptome is not yet fully elucidated. We report a high-throughput sequence of the human transcriptome from a human embryonic kidney and a B cell line. We used shotgun sequencing of transcripts to generate randomly distributed reads.

Nitric oxide-responsive genes and promoters in Arabidopsis thaliana: a bioinformatics approach.

Due to its high reactivity and its ability to diffuse and permeate the cell membrane, nitric oxide (NO) and its exchangeable redox-activated species are unique biological messengers in animals and in plants. Although an increasing number of reports indicate that NO is an essential molecule in several physiological processes, there is not a clear picture of its method of action. Studies on the transcriptional changes induced by NO permitted identification of genes involved in different functional processes such as signal transduction, defence and cell death, transport, basic metabolism, and reactive oxygen species (ROS) production and degradation.

The next generation of literature analysis: integration of genomic analysis into text mining.

Text-mining systems are indispensable tools to reduce the increasing flux of information in scientific literature to topics pertinent to a particular interest in focus. Most of the scientific literature is published as unstructured free text, complicating the development of data processing tools, which rely on structured information. To overcome the problems of free text analysis, structured, hand-curated information derived from literature is integrated in text-mining systems to improve precision and recall.

Multievidence microarray mining.

Microarray mining is a challenging task because of the superposition of several processes in the data. We believe that the combination of microarray data-based analyses (statistical significance analysis of gene expression) with array-independent analyses (literature-mining and promoter analysis) enables some of the problems of traditional array analysis to be overcome. As a proof-of-principle, we revisited publicly available microarray data derived from an experiment with platelet-derived growth factor (PDGF)-stimulated fibroblasts.