Controlling and visualizing Dirac physics in topological semimetal heterostructures.

A bulk crystal of cadmium arsenide is a three-dimensional Dirac semimetal, but, in a thin film, it can behave like a three-dimensional topological insulator. This tunability provides unique opportunities to manipulate and explore a topological insulator phase. However, an obstacle to engineering such tunability is the subtlety of transport-based discriminants for topological phases. In this work, the quantum capacitance of cadmium arsenide-based heterostructures provides two direct experimental signatures of three-dimensional topological insulator physics: an insulating three-dimensional bulk and a Landau level at zero energy that does not disperse in a magnetic field. We proceed to join our ability to see these fingerprints of the topological surface states with flexibility afforded by our epitaxial heterostructures to demonstrate a route toward controlling the energy of the Dirac nodes on each surface. These results point to new avenues for engineering topological insulators based on cadmium arsenide.

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosis.

Nowadays, the massive amount of data generated by modern sequencing technologies provides an unprecedented opportunity to find genes associated with cancer patient prognosis, connecting basic and translational research. However, treating high dimensionality of gene expression data and integrating it with clinical variables are major challenges to perform these analyses. Here, we present Reboot, an integrative approach to find and validate genes and transcripts (splicing isoforms) associated with cancer patient prognosis from high dimensional expression datasets. Reboot innovates by using a multivariate strategy with penalized Cox regression (LASSO method) combined with a bootstrap approach, in addition to statistical tests and plots to support the findings. Applying Reboot on data from 154 glioblastoma patients, we identified a three-gene signature (IKBIP, OSMR, PODNL1) whose increased derived risk score was significantly associated with worse patients' prognosis. Similarly, Reboot was able to find a seven-splicing isoforms signature related to worse overall survival in 177 pancreatic adenocarcinoma patients with elevated risk scores after uni- and multivariate analyses. In summary, Reboot is an efficient, intuitive and straightforward way of finding genes or splicing isoforms signatures relevant to patient prognosis, which can democratize this kind of analysis and shed light on still under-investigated cancer-related genes and splicing isoforms.

MiRIAD update: using alternative polyadenylation, protein interaction network analysis and additional species to enhance exploration of the role of intragenic miRNAs and their host genes.

Database URL: http://www.miriad-database.org.

miRIAD-integrating microRNA inter- and intragenic data.

MicroRNAs (miRNAs) are a class of small (∼22 nucleotides) non-coding RNAs that post-transcriptionally regulate gene expression by interacting with target mRNAs. A majority of miRNAs is located within intronic or exonic regions of protein-coding genes (host genes), and increasing evidence suggests a functional relationship between these miRNAs and their host genes. Here, we introduce miRIAD, a web-service to facilitate the analysis of genomic and structural features of intragenic miRNAs and their host genes for five species (human, rhesus monkey, mouse, chicken and opossum). miRIAD contains the genomic classification of all miRNAs (inter- and intragenic), as well as classification of all protein-coding genes into host or non-host genes (depending on whether they contain an intragenic miRNA or not). We collected and processed public data from several sources to provide a clear visualization of relevant knowledge related to intragenic miRNAs, such as host gene function, genomic context, names of and references to intragenic miRNAs, miRNA binding sites, clusters of intragenic miRNAs, miRNA and host gene expression across different tissues and expression correlation for intragenic miRNAs and their host genes. Protein-protein interaction data are also presented for functional network analysis of host genes. In summary, miRIAD was designed to help the research community to explore, in a user-friendly environment, intragenic miRNAs, their host genes and functional annotations with minimal effort, facilitating hypothesis generation and in-silico validations. Database URL: http://www.miriad-database.org.

SPLOOCE: a new portal for the analysis of human splicing variants.

Understanding alternative splicing is crucial to elucidate the mechanisms behind several biological phenomena, including diseases. The huge amount of expressed sequences available nowadays represents an opportunity and a challenge to catalog and display alternative splicing events (ASEs). Although several groups have faced this challenge with relative success, we still lack a computational tool that uses a simple and straightforward method to retrieve, name and present ASEs. Here we present SPLOOCE, a portal for the analysis of human splicing variants. SPLOOCE uses a method based on regular expressions for retrieval of ASEs. We propose a simple syntax that is able to capture the complexity of ASEs.

SurfaceomeDB: a cancer-orientated database for genes encoding cell surface proteins.

Cell surface proteins (CSPs) are excellent targets for the development of diagnostic and therapeutic reagents, and it is estimated that 10-20% of all genes in the human genome encode CSPs. In an effort to integrate all data publicly available for genes encoding cell surface proteins, a database (SurfaceomeDB) was developed. SurfaceomeDB is a gene-centered portal containing different types of information, including annotation for gene expression, protein domains, somatic mutations in cancer, and protein-protein interactions for all human genes encoding CSPs. SurfaceomeDB was implemented as an integrative and relational database in a user-friendly web interface, where users can search for gene name, gene annotation, or keywords. There is also a streamlined graphical representation of all data provided and links to the most important data repositories and databases, such as NCBI, UCSC Genome Browser, and EBI.