Querying the public databases for sequences using complex keywords contained in the feature lines

BACKGROUND: High throughput technologies often require the retrieval of large data sets of sequences. Retrieval of EMBL or GenBank entries using keywords is easy using tools such as ACNUC, Entrez or SRS, but has some limitations, in particular when querying with complex keywords. RESULTS: We show that Entrez has severe limitations with respect to retrieving subsequences. SRS works well with simple keywords but not with keywords composed of several terms, and has problems with complex queries. ACNUC works well, but does not allow precise queries in the Feature qualifiers. We developed specific Perl scripts to precisely retrieve subsequences as defined by complex descriptors in the Features qualifiers of the EMBL entries. We improved parts of the bioPerl library to allow parsing of large data files, and we embedded these scripts in a user friendly interface (OS independent) for easy use. CONCLUSION: Although not as fast as the public tools that use prebuilt indexes, parsing the complete entries using a script is often necessary in order to retrieve the exact data searched for. Embedding in a user friendly interface allows biologists to use the scripts, which can easily be modified, if necessary, by bioinformaticians for unforeseen needs

Targeted electroporation of defined lateral ventricular walls: a novel and rapid method to study fate specification during postnatal forebrain neurogenesis

<p>Abstract</p> <p>Background</p> <p>Postnatal olfactory bulb (OB) neurogenesis involves the generation of granule and periglomerular cells by neural stem cells (NSCs) located in the walls of the lateral ventricle (LV). Recent studies show that NSCs located in different regions of the LV give rise to different types of OB neurons. However, the molecular mechanisms governing neuronal specification remain largely unknown and new methods to approach these questions are needed.</p> <p>Results</p> <p>In this study, we refine electroporation of the postnatal forebrain as a technique to perform precise and accurate delivery of transgenes to NSCs located in distinct walls of the LV in the mouse. Using this method, we confirm and expand previous studies showing that NSCs in distinct walls of the LV produce neurons that invade different layers of the OB. Fate mapping of the progeny of radial glial cells located in these distinct LV walls reveals their specification into defined subtypes of granule and periglomerular neurons.</p> <p>Conclusions</p> <p>Our results provide a baseline with which future studies aiming at investigating the role of factors in postnatal forebrain neuronal specification can be compared. Targeted electroporation of defined LV NSC populations will prove valuable to study the genetic factors involved in forebrain neuronal specification.</p

Pan-genomic analysis to redefine species and subspecies based on quantum discontinuous variation: the Klebsiella paradigm

International audienceBackground: Various methods are currently used to define species and are based on the phylogenetic marker 16S ribosomal RNA gene sequence, DNA-DNA hybridization and DNA GC content. However, these are restricted genetic tools and showed significant limitations. Results: In this work, we describe an alternative method to build taxonomy by analyzing the pan-genome composition of different species of the Klebsiella genus. Klebsiella species are Gram-negative bacilli belonging to the large Enterobacteriaceae family. Interestingly, when comparing the core/pan-genome ratio; we found a clear discontinuous variation that can define a new species. Conclusions: Using this pan-genomic approach, we showed that Klebsiella pneumoniae subsp. ozaenae and Klebsiella pneumoniae subsp. rhinoscleromatis are species of the Klebsiella genus, rather than subspecies of Klebsiella pneumoniae. This pan-genomic analysis, helped to develop a new tool for defining species introducing a quantic perspective for taxonomy

Genome Wide Identification of Recessive Cancer Genes by Combinatorial Mutation Analysis

We devised a novel procedure to identify human cancer genes acting in a recessive manner. Our strategy was to combine the contributions of the different types of genetic alterations to loss of function: amino-acid substitutions, frame-shifts, gene deletions. We studied over 20,000 genes in 3 Gigabases of coding sequences and 700 array comparative genomic hybridizations. Recessive genes were scored according to nucleotide mismatches under positive selective pressure, frame-shifts and genomic deletions in cancer. Four different tests were combined together yielding a cancer recessive p-value for each studied gene. One hundred and fifty four candidate recessive cancer genes (p-value<1.5×10−7, FDR = 0.39) were identified. Strikingly, the prototypical cancer recessive genes TP53, PTEN and CDKN2A all ranked in the top 0.5% genes. The functions significantly affected by cancer mutations are exactly overlapping those of known cancer genes, with the critical exception for the absence of tyrosine kinases, as expected for a recessive gene-set

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\mathrm{t}\overline{\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV)

Search for heavy resonances decaying to a top quark and a bottom quark in the lepton+jets final state in proton–proton collisions at 13 TeV

info:eu-repo/semantics/publishe

Evidence for the Higgs boson decay to a bottom quark–antiquark pair

info:eu-repo/semantics/publishe