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News Article | March 7, 2017
Site: www.techtimes.com

The Volkswagen Group (VW Group) is set to throw the gauntlet to Apple and Google with its very own concept autonomous car. On March 6, at the Geneva International Motor Show, VW took the wraps of its concept self-driving card dubbed the Sedric. "The future of mobility is vibrant, colorful and fascinating. With Sedric we are looking far ahead: the study demonstrates how a new, integrated mobility system of the future could function," said Matthias Müller, CEO of the VW Group. The arrival of the Sedric, however, may not give sleepless nights to Google and Apple who are working on their own self-driving cars as it will remain confined to being a concept. Sedric is the first-ever concept vehicle from VW Group and the company asserts it is "a trailblazer and idea platform for autonomous driving." While the concept car may not release to market, several functions and elements included in the vehicle may make their way eventually to VW cars in the near future per the company's CEO. An unusual feature of the Sedric is that it contains no steering wheel, pedals or cockpit. VW stated that Sedric could perform as a "friend of companion" and it will resemble the look of the Level Five autonomous vehicles (the highest stage of automation). The futuristic looking car also has sixth sense ability as the Sedric is equipped with seven cameras and five lidar sensors. These features are there to support the car to be conscious about the things around it and to avoid accidents. You can give a signal to Sedric by using an exclusive key called OneButton. If you press it, the button will deliver a signal to the car and it will arrive at your door like an autonomous Uber. Also, after getting in the car you can interact with the vehicle through voice command. The operator can ask Sedric to set a terminal point, to select a certain route and also to plan breaks on a journey. The all-electric Sedric's interiors are quite spacious and offers seating for four passengers, but there will be no driver. VW assumes Sedric will be perfect for everyone whether a single person, families or for a shared ride. There are several questions about the idea of this kind of vehicle and its ability to do everything without any guidance from a human. Therefore, it is still unclear whether Sedric can achieve the level required to be branded Level Five. VW is putting all efforts and spending a huge sum of money for the sake of autonomous technology's further development. Muller said that Sedric provides the real image of the future autonomous cars today and VW Group is convinced that fully-automated cars will make city lives better thanks to their eco-friendly characteristics. Moreover, the futuristic technology also assures safety. If you want to have a look at Sedric then check out the video below. © 2017 Tech Times, All rights reserved. Do not reproduce without permission.


PubMed | Japan National Institute of Advanced Industrial Science and Technology, Okinawa Institute of Science and Technology, PharmaDesign Inc., Tokyo Institute of Technology and 10 more.
Type: | Journal: Scientific reports | Year: 2015

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.


Shirai H.,Astellas Pharma Inc. | Ikeda K.,Japan National Institute of Biomedical Innovation | Ikeda K.,Level Five Co. | Yamashita K.,Osaka University | And 8 more authors.
Proteins: Structure, Function and Bioinformatics | Year: 2014

In the second antibody modeling assessment, we used a semiautomated template-based structure modeling approach for 11 blinded antibody variable region (Fv) targets. The structural modeling method involved several steps, including template selection for framework and canonical structures of complementary determining regions (CDRs), homology modeling, energy minimization, and expert inspection. The submitted models for Fv modeling in Stage 1 had the lowest average backbone root mean square deviation (RMSD) (1.06 Å). Comparison to crystal structures showed the most accurate Fv models were generated for 4 out of 11 targets. We found that the successful modeling in Stage 1 mainly was due to expert-guided template selection for CDRs, especially for CDR-H3, based on our previously proposed empirical method (H3-rules) and the use of position specific scoring matrix-based scoring. Loop refinement using fragment assembly and multicanonical molecular dynamics (McMD) was applied to CDR-H3 loop modeling in Stage 2. Fragment assembly and McMD produced putative structural ensembles with low free energy values that were scored based on the OSCAR all-atom force field and conformation density in principal component analysis space, respectively, as well as the degree of consensus between the two sampling methods. The quality of 8 out of 10 targets improved as compared with Stage 1. For 4 out of 10 Stage-2 targets, our method generated top-scoring models with RMSD values of less than 1 Å. In this article, we discuss the strengths and weaknesses of our approach as well as possible directions for improvement to generate better predictions in the future. © 2014 Wiley Periodicals, Inc.


Nagano N.,Japan National Institute of Advanced Industrial Science and Technology | Nakayama N.,Japan National Institute of Advanced Industrial Science and Technology | Ikeda K.,Level Five Co. | Fukuie M.,Level Five Co. | And 5 more authors.
Nucleic Acids Research | Year: 2015

The EzCatDB database (http://ezcatdb.cbrc.jp/EzCatDB/) has emphasized manual classification of enzyme reactions from the viewpoints of enzyme active-site structures and their catalytic mechanisms based on literature information, amino acid sequences of enzymes (UniProtKB) and the corresponding tertiary structures from the Protein Data Bank (PDB). Reaction types such as hydrolysis, transfer, addition, elimination, isomerization, hydride transfer and electron transfer have been included in the reaction classification, RLCP. This database includes information related to ligand molecules on the enzyme structures in the PDB data, classified in terms of cofactors, substrates, products and intermediates, which are also necessary to elucidate the catalytic mechanisms. Recently, the database system was updated. The 3D structures of active sites for each PDB entry can be viewed using Jmol or Rasmol software. Moreover, sequence search systems of two types were developed for the Ez-CatDB database: EzCat-BLAST and EzCat-FORTE. EzCat-BLAST is suitable for quick searches, adopting the BLAST algorithm, whereas EzCat-FORTE is more suitable for detecting remote homologues, adopting the algorithm for FORTE protein structure prediction software. Another system, EzMetAct, is also available to searching for major active-site structures in EzCatDB, for which PDB-formatted queries can be searched. © The Author(s) 2014.


Chen Y.-A.,Japan National Institute of Biomedical Innovation | Tripathi L.P.,Japan National Institute of Biomedical Innovation | Dessailly B.H.,Japan National Institute of Biomedical Innovation | Dessailly B.H.,Takeda Cambridge | And 5 more authors.
PLoS ONE | Year: 2014

Prioritising candidate genes for further experimental characterisation is an essential, yet challenging task in biomedical research. One way of achieving this goal is to identify specific biological themes that are enriched within the gene set of interest to obtain insights into the biological phenomena under study. Biological pathway data have been particularly useful in identifying functional associations of genes and/or gene sets. However, biological pathway information as compiled in varied repositories often differs in scope and content, preventing a more effective and comprehensive characterisation of gene sets. Here we describe a new approach to constructing biologically coherent gene sets from pathway data in major public repositories and employing them for functional analysis of large gene sets. We first revealed significant overlaps in gene content between different pathways and then defined a clustering method based on the shared gene content and the similarity of gene overlap patterns. We established the biological relevance of the constructed pathway clusters using independent quantitative measures and we finally demonstrated the effectiveness of the constructed pathway clusters in comparative functional enrichment analysis of gene sets associated with diverse human diseases gathered from the literature. The pathway clusters and gene mappings have been integrated into the TargetMine data warehouse and are likely to provide a concise, manageable and biologically relevant means of functional analysis of gene sets and to facilitate candidate gene prioritisation. © 2014 Chen et al.


PubMed | Japan National Institute of Advanced Industrial Science and Technology, Level Five Co. and Ochanomizu University
Type: Journal Article | Journal: Nucleic acids research | Year: 2015

The EzCatDB database (http://ezcatdb.cbrc.jp/EzCatDB/) has emphasized manual classification of enzyme reactions from the viewpoints of enzyme active-site structures and their catalytic mechanisms based on literature information, amino acid sequences of enzymes (UniProtKB) and the corresponding tertiary structures from the Protein Data Bank (PDB). Reaction types such as hydrolysis, transfer, addition, elimination, isomerization, hydride transfer and electron transfer have been included in the reaction classification, RLCP. This database includes information related to ligand molecules on the enzyme structures in the PDB data, classified in terms of cofactors, substrates, products and intermediates, which are also necessary to elucidate the catalytic mechanisms. Recently, the database system was updated. The 3D structures of active sites for each PDB entry can be viewed using Jmol or Rasmol software. Moreover, sequence search systems of two types were developed for the EzCatDB database: EzCat-BLAST and EzCat-FORTE. EzCat-BLAST is suitable for quick searches, adopting the BLAST algorithm, whereas EzCat-FORTE is more suitable for detecting remote homologues, adopting the algorithm for FORTE protein structure prediction software. Another system, EzMetAct, is also available to searching for major active-site structures in EzCatDB, for which PDB-formatted queries can be searched.

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