Migrant entrepreneurship support in Europe: a PRISMA systematic literature review.

Background: This systematic literature review (SLR) analyzes migrant entrepreneurship support in Europe through three research questions (RQs) to understand 1) migrant entrepreneur characteristics in the European context, 2) challenges encountered by migrant entrepreneurs in European host countries, and 3) policies supporting migrant entrepreneurship in Europe. This review addresses gaps in current knowledge in academia as well as issues that policymakers and practitioners face when addressing migrant entrepreneurship support.

Methods: This SLR employed a search protocol to retrieve published sources from 1970 to 2021, via Scopus (27 March 2022) and Web of Science (7 April 2022).

Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR.

Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance.

Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer.

Resistance to EGFR inhibitors (EGFRi) presents a major obstacle in treating non-small cell lung cancer (NSCLC). One of the most exciting new ways to find potential resistance markers involves running functional genetic screens, such as CRISPR, followed by manual triage of significantly enriched genes. This triage process to identify 'high value' hits resulting from the CRISPR screen involves manual curation that requires specialized knowledge and can take even experts several months to comprehensively complete.

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care - Preliminary Report.

Background: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.

CNEr: A toolkit for exploring extreme noncoding conservation.

Conserved Noncoding Elements (CNEs) are elements exhibiting extreme noncoding conservation in Metazoan genomes. They cluster around developmental genes and act as long-range enhancers, yet nothing that we know about their function explains the observed conservation levels. Clusters of CNEs coincide with topologically associating domains (TADs), indicating ancient origins and stability of TAD locations.

Introduction of 'Generalized Genomic Signatures' for the quantification of neighbour preferences leads to taxonomy- and functionality-based distinction among sequences.

Analysis of DNA composition at several length scales constitutes the bulk of many early studies aimed at unravelling the complexity of the organization and functionality of genomes. Dinucleotide relative abundances are considered an idiosyncratic feature of genomes, regarded as a 'genomic signature'. Motivated by this finding, we introduce the 'Generalized Genomic Signatures' (GGSs), composed of over- and under-abundances of all oligonucleotides of a given length, thus filtering out compositional trends and neighbour preferences at any shorter range.

CNEFinder: finding conserved non-coding elements in genomes.

Motivation: Conserved non-coding elements (CNEs) represent an enigmatic class of genomic elements which, despite being extremely conserved across evolution, do not encode for proteins. Their functions are still largely unknown. Thus, there exists a need to systematically investigate their roles in genomes.

Conserved non-coding elements: developmental gene regulation meets genome organization.

Comparative genomics has revealed a class of non-protein-coding genomic sequences that display an extraordinary degree of conservation between two or more organisms, regularly exceeding that found within protein-coding exons. These elements, collectively referred to as conserved non-coding elements (CNEs), are non-randomly distributed across chromosomes and tend to cluster in the vicinity of genes with regulatory roles in multicellular development and differentiation. CNEs are organized into functional ensembles called genomic regulatory blocks-dense clusters of elements that collectively coordinate the expression of shared target genes, and whose span in many cases coincides with topologically associated domains.

On avoided words, absent words, and their application to biological sequence analysis.

Background: The deviation of the observed frequency of a word from its expected frequency in a given sequence is used to determine whether or not the word is . This concept is particularly useful in DNA linguistic analysis. The value of the deviation of , denoted by [Formula: see text], effectively characterises the extent of a word by its edge contrast in the context in which it occurs.

Fractality and entropic scaling in the chromosomal distribution of conserved noncoding elements in the human genome.

Conserved non-coding elements (CNEs) are defined using various degrees of sequence identity and thresholds of minimal length. Their conservation frequently exceeds the one observed for protein-coding sequences. We explored the chromosomal distribution of different classes of CNEs in the human genome.

An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition.

Background: This article provides an overview of the first BIOASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March and September 2013. BIOASQ assesses the ability of systems to semantically index very large numbers of biomedical scientific articles, and to return concise and user-understandable answers to given natural language questions by combining information from biomedical articles and ontologies.

Results: The 2013 BIOASQ competition comprised two tasks, Task 1a and Task 1b.

Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers.

Scarce work has been done in the analysis of the composition of conserved non-coding elements (CNEs) that are identified by comparisons of two or more genomes and are found to exist in all metazoan genomes. Here we present the analysis of CNEs with a methodology that takes into account word occurrence at various lengths scales in the form of feature vector representation and rule based classifiers. We implement our approach on both protein-coding exons and CNEs, originating from human, insect (Drosophila melanogaster) and worm (Caenorhabditis elegans) genomes, that are either identified in the present study or obtained from the literature.

Conserved noncoding elements follow power-law-like distributions in several genomes as a result of genome dynamics.

Conserved, ultraconserved and other classes of constrained elements (collectively referred as CNEs here), identified by comparative genomics in a wide variety of genomes, are non-randomly distributed across chromosomes. These elements are defined using various degrees of conservation between organisms and several thresholds of minimal length. We here investigate the chromosomal distribution of CNEs by studying the statistical properties of distances between consecutive CNEs.