Institution
Pompeu Fabra University
Education•Barcelona, Spain•
About: Pompeu Fabra University is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Population & Gene. The organization has 8093 authors who have published 23570 publications receiving 858431 citations. The organization is also known as: Universitat Pompeu Fabra & UPF.
Topics: Population, Gene, European union, Genome, Context (language use)
Papers published on a yearly basis
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TL;DR: The comprehensiveness of the GENCODE annotation was assessed by attempting to validate all the predicted exon boundaries outside the GencODE annotation, which showed only 40% of GENCode exons are contained within the two sets, which is a reflection of the high number of alternative splice forms with unique exons annotated.
Abstract: Background
The GENCODE consortium was formed to identify and map all protein-coding genes within the ENCODE regions. This was achieved by a combination of initial manual annotation by the HAVANA team, experimental validation by the GENCODE consortium and a refinement of the annotation based on these experimental results.
619 citations
Whitney Laboratory for Marine Bioscience1, Auburn University2, Florida State University3, Pompeu Fabra University4, University of Massachusetts Medical School5, University of Illinois at Urbana–Champaign6, University of Groningen7, Sunnybrook Research Institute8, Russian Academy of Sciences9, University of Florida10, Genetic Information Research Institute11, University of Washington12, Royal Holloway, University of London13, Catalan Institution for Research and Advanced Studies14
TL;DR: The draft genome of Pleurobrachia bachei, Pacific sea gooseberry, together with ten other ctenophore transcriptomes, are presented, and show that they are remarkably distinct from other animal genomes in their content of neurogenic, immune and developmental genes.
Abstract: The origins of neural systems remain unresolved. In contrast to other basal metazoans, ctenophores (comb jellies) have both complex nervous and mesoderm-derived muscular systems. These holoplanktonic predators also have sophisticated ciliated locomotion, behaviour and distinct development. Here we present the draft genome of Pleurobrachia bachei, Pacific sea gooseberry, together with ten other ctenophore transcriptomes, and show that they are remarkably distinct from other animal genomes in their content of neurogenic, immune and developmental genes. Our integrative analyses place Ctenophora as the earliest lineage within Metazoa. This hypothesis is supported by comparative analysis of multiple gene families, including the apparent absence of HOX genes, canonical microRNA machinery, and reduced immune complement in ctenophores. Although two distinct nervous systems are well recognized in ctenophores, many bilaterian neuron-specific genes and genes of 'classical' neurotransmitter pathways either are absent or, if present, are not expressed in neurons. Our metabolomic and physiological data are consistent with the hypothesis that ctenophore neural systems, and possibly muscle specification, evolved independently from those in other animals.
610 citations
TL;DR: Transient transfections of different mutants demonstrated that Tyr-654 is phosphorylated in conditions in which adherens junctions are disrupted and evidenced that binding ofβ-catenin to E-cadherin in vivo is controlled by phosphorylation of β- catenin Tyr-652.
610 citations
TL;DR: It is reported that cooperative cation-π interactions between tyrosines in the LC domain and arginines in structured C-terminal domains also contribute to phase separation, and transportin acts as a physiological molecular chaperone of FUS in neuron terminals, reducing phase separation and gelation of methylated and hypomethylated FUS and rescuing protein synthesis.
606 citations
TL;DR: This tutorial introduces the techniques that are used to obtain results in the form of so-called error bounds in statistical learning theory.
Abstract: The goal of statistical learning theory is to study, in a statistical framework, the properties of learning algorithms. In particular, most results take the form of so-called error bounds. This tutorial introduces the techniques that are used to obtain such results.
602 citations
Authors
Showing all 8248 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Andrei Shleifer | 171 | 514 | 271880 |
| Paul Elliott | 153 | 773 | 103839 |
| Bert Brunekreef | 124 | 806 | 81938 |
| Philippe Aghion | 122 | 507 | 73438 |
| Anjana Rao | 118 | 337 | 61395 |
| Jordi Sunyer | 115 | 798 | 57211 |
| Kenneth J. Arrow | 113 | 411 | 111221 |
| Xavier Estivill | 110 | 673 | 59568 |
| Roderic Guigó | 108 | 304 | 106914 |
| Mark J. Nieuwenhuijsen | 107 | 647 | 49080 |
| Jordi Alonso | 107 | 523 | 64058 |
| Alfonso Valencia | 106 | 542 | 55192 |
| Luis Serrano | 105 | 452 | 42515 |
| Vadim N. Gladyshev | 102 | 490 | 34148 |
| Josep M. Antó | 100 | 493 | 38663 |