Research Organization of Information and Systems

The combination of significantly lower cost and increased speed of sequencing has resulted in an explosive growth of data submitted into the primary next-generation sequence data archive, the Sequence Read Archive (SRA). The preservation of experimental data is an important part of the scientific record, and increasing numbers of journals and funding agencies require that next-generation sequence data are deposited into the SRA. The SRA was established as a public repository for the next-generation sequence data and is operated by the International Nucleotide Sequence Database Collaboration (INSDC). INSDC partners include the National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). The SRA is accessible at http://www.ncbi.nlm.nih.gov/Traces/sra from NCBI, at http://www.ebi.ac.uk/ena from EBI and at http://trace.ddbj.nig.ac.jp from DDBJ. In this article, we present the content and structure of the SRA, detail our support for sequencing platforms and provide recommended data submission levels and formats. We also briefly outline our response to the challenge of data growth.

In this paper we discuss augmented reality (AR) displays in a general sense, within the context of a reality-virtuality (RV) continuum, encompassing a large class of `mixed reality' (MR) displays, which also includes augmented virtuality (AV). MR displays are defined by means of seven examples of existing display concepts in which real objects and virtual objects are juxtaposed. Essential factors which distinguish different MR display systems from each other are presented, first by means of a table in which the nature of the underlying scene, how it is viewed, and the observer's reference to it are compared, and then by means of a three dimensional taxonomic framework comprising: extent of world knowledge, reproduction fidelity, and extent of presence metaphor. A principal objective of the taxonomy is to clarify terminology issues and to provide a framework for classifying research across different disciplines.

A method for extracting information about facial expressions from images is presented. Facial expression images are coded using a multi-orientation multi-resolution set of Gabor filters which are topographically ordered and aligned approximately with the face. The similarity space derived from this representation is compared with one derived from semantic ratings of the images by human observers. The results show that it is possible to construct a facial expression classifier with Gabor coding of the facial images as the input stage. The Gabor representation shows a significant degree of psychological plausibility, a design feature which may be important for human-computer interfaces.

SUMMARY: KofamKOALA is a web server to assign KEGG Orthologs (KOs) to protein sequences by homology search against a database of profile hidden Markov models (KOfam) with pre-computed adaptive score thresholds. KofamKOALA is faster than existing KO assignment tools with its accuracy being comparable to the best performing tools. Function annotation by KofamKOALA helps linking genes to KEGG resources such as the KEGG pathway maps and facilitates molecular network reconstruction. AVAILABILITY AND IMPLEMENTATION: KofamKOALA, KofamScan and KOfam are freely available from GenomeNet (https://www.genome.jp/tools/kofamkoala/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Abstract Summary: CRISPRdirect is a simple and functional web server for selecting rational CRISPR/Cas targets from an input sequence. The CRISPR/Cas system is a promising technique for genome engineering which allows target-specific cleavage of genomic DNA guided by Cas9 nuclease in complex with a guide RNA (gRNA), that complementarily binds to a ∼20 nt targeted sequence. The target sequence requirements are twofold. First, the 5′-NGG protospacer adjacent motif (PAM) sequence must be located adjacent to the target sequence. Second, the target sequence should be specific within the entire genome in order to avoid off-target editing. CRISPRdirect enables users to easily select rational target sequences with minimized off-target sites by performing exhaustive searches against genomic sequences. The server currently incorporates the genomic sequences of human, mouse, rat, marmoset, pig, chicken, frog, zebrafish, Ciona, fruit fly, silkworm, Caenorhabditis elegans, Arabidopsis, rice, Sorghum and budding yeast. Availability: Freely available at http://crispr.dbcls.jp/. Contact: y-naito@dbcls.rois.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online.

Summary: We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 min, with rich information such as pseudogenes, translation exceptions and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future. Availability and implementation: The software is implemented in Python 3 and runs in both Python 2.7 and 3.4-on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/. Contact: yn@nig.ac.jp. Supplementary information: Supplementary data are available at Bioinformatics online.

We propose a method for automatically classifying facial images based on labeled elastic graph matching, a 2D Gabor wavelet representation, and linear discriminant analysis. Results of tests with three image sets are presented for the classification of sex, "race", and expression. A visual interpretation of the discriminant vectors is provided.

This article presents a reinforcement learning framework for continuous-time dynamical systems without a priori discretization of time, state, and action. Based on the Hamilton-Jacobi-Bellman (HJB) equation for infinite-horizon, discounted reward problems, we derive algorithms for estimating value functions and improving policies with the use of function approximators. The process of value function estimation is formulated as the minimization of a continuous-time form of the temporal difference (TD) error. Update methods based on backward Euler approximation and exponential eligibility traces are derived, and their correspondences with the conventional residual gradient, TD(0), and TD(lambda) algorithms are shown. For policy improvement, two methods-a continuous actor-critic method and a value-gradient-based greedy policy-are formulated. As a special case of the latter, a nonlinear feedback control law using the value gradient and the model of the input gain is derived. The advantage updating, a model-free algorithm derived previously, is also formulated in the HJB-based framework. The performance of the proposed algorithms is first tested in a nonlinear control task of swinging a pendulum up with limited torque. It is shown in the simulations that (1) the task is accomplished by the continuous actor-critic method in a number of trials several times fewer than by the conventional discrete actor-critic method; (2) among the continuous policy update methods, the value-gradient-based policy with a known or learned dynamic model performs several times better than the actor-critic method; and (3) a value function update using exponential eligibility traces is more efficient and stable than that based on Euler approximation. The algorithms are then tested in a higher-dimensional task: cart-pole swing-up. This task is accomplished in several hundred trials using the value-gradient-based policy with a learned dynamic model.

New generation sequencing platforms are producing data with significantly higher throughput and lower cost. A portion of this capacity is devoted to individual and community scientific projects. As these projects reach publication, raw sequencing datasets are submitted into the primary next-generation sequence data archive, the Sequence Read Archive (SRA). Archiving experimental data is the key to the progress of reproducible science. The SRA was established as a public repository for next-generation sequence data as a part of the International Nucleotide Sequence Database Collaboration (INSDC). INSDC is composed of the National Center for Biotechnology Information (NCBI), the European Bioinformatics Institute (EBI) and the DNA Data Bank of Japan (DDBJ). The SRA is accessible at www.ncbi.nlm.nih.gov/sra from NCBI, at www.ebi.ac.uk/ena from EBI and at trace.ddbj.nig.ac.jp from DDBJ. In this article, we present the content and structure of the SRA and report on updated metadata structures, submission file formats and supported sequencing platforms. We also briefly outline our various responses to the challenge of explosive data growth.

The ProteomeXchange (PX) Consortium of proteomics resources (http://www.proteomexchange.org) was formally started in 2011 to standardize data submission and dissemination of mass spectrometry proteomics data worldwide. We give an overview of the current consortium activities and describe the advances of the past few years. Augmenting the PX founding members (PRIDE and PeptideAtlas, including the PASSEL resource), two new members have joined the consortium: MassIVE and jPOST. ProteomeCentral remains as the common data access portal, providing the ability to search for data sets in all participating PX resources, now with enhanced data visualization components.We describe the updated submission guidelines, now expanded to include four members instead of two. As demonstrated by data submission statistics, PX is supporting a change in culture of the proteomics field: public data sharing is now an accepted standard, supported by requirements for journal submissions resulting in public data release becoming the norm. More than 4500 data sets have been submitted to the various PX resources since 2012. Human is the most represented species with approximately half of the data sets, followed by some of the main model organisms and a growing list of more than 900 diverse species. Data reprocessing activities are becoming more prominent, with both MassIVE and PeptideAtlas releasing the results of reprocessed data sets. Finally, we outline the upcoming advances for ProteomeXchange.

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

Silencing of transposable elements occurs during fetal gametogenesis in males via de novo DNA methylation of their regulatory regions. The loss of MILI (miwi-like) and MIWI2 (mouse piwi 2), two mouse homologs of Drosophila Piwi, activates retrotransposon gene expression by impairing DNA methylation in the regulatory regions of the retrotransposons. However, as it is unclear whether the defective DNA methylation in the mutants is due to the impairment of de novo DNA methylation, we analyze DNA methylation and Piwi-interacting small RNA (piRNA) expression in wild-type, MILI-null, and MIWI2-null male fetal germ cells. We reveal that defective DNA methylation of the regulatory regions of the Line-1 (long interspersed nuclear elements) and IAP (intracisternal A particle) retrotransposons in the MILI-null and MIWI2-null male germ cells takes place at the level of de novo methylation. Comprehensive analysis shows that the piRNAs of fetal germ cells are distinct from those previously identified in neonatal and adult germ cells. The expression of piRNAs is reduced under MILI- and MIWI2-null conditions in fetal germ cells, although the extent of the reduction differs significantly between the two mutants. Our data strongly suggest that MILI and MIWI2 play essential roles in establishing de novo DNA methylation of retrotransposons in fetal male germ cells.

Mass spectrometry (MS) is by far the most used experimental approach in high-throughput proteomics. The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) was originally set up to standardize data submission and dissemination of public MS proteomics data. It is now 10 years since the initial data workflow was implemented. In this manuscript, we describe the main developments in PX since the previous update manuscript in Nucleic Acids Research was published in 2020. The six members of the Consortium are PRIDE, PeptideAtlas (including PASSEL), MassIVE, jPOST, iProX and Panorama Public. We report the current data submission statistics, showcasing that the number of datasets submitted to PX resources has continued to increase every year. As of June 2022, more than 34 233 datasets had been submitted to PX resources, and from those, 20 062 (58.6%) just in the last three years. We also report the development of the Universal Spectrum Identifiers and the improvements in capturing the experimental metadata annotations. In parallel, we highlight that data re-use activities of public datasets continue to increase, enabling connections between PX resources and other popular bioinformatics resources, novel research and also new data resources. Finally, we summarise the current state-of-the-art in data management practices for sensitive human (clinical) proteomics data.

This study investigated the effects of training in/r/-/l/ perceptual identification on /r/-/l/ production by adult Japanese speakers. Subjects were recorded producing English words that contrast /r/ and /l/ before and after participating in an extended period of /r/-/l/ identification training using a high-variability presentation format. All subjects showed significant perceptual learning as a result of the training program, and this perceptual learning generalized to novel items spoken by new talkers. Improvement in the Japanese trainees' /r/-/l/ spoken utterances as a consequence of perceptual training was evaluated using two separate tests with native English listeners. First, a direct comparison of the pretest and post-test tokens showed significant improvement in the perceived rating of /r/ and /l/ productions as a consequence of perceptual learning. Second, the post-test productions were more accurately identified by English listeners than the pretest productions in a two-alternative minimal-pair identification procedure. These results indicate that the knowledge gained during perceptual learning of /r/ and /l/ transferred to the production domain, and thus provides novel information regarding the relationship between speech perception and production.

Presents an approach to movement planning, on-line trajectory modification, and imitation learning by representing movement plans based on a set of nonlinear differential equations with well-defined attractor dynamics. The resultant movement plan remains an autonomous set of nonlinear differential equations that forms a control policy (CP) which is robust to strong external perturbations and that can be modified on-line by additional perceptual variables. We evaluate the system with a humanoid robot simulation and an actual humanoid robot. Experiments are presented for the imitation of three types of movements: reaching movements with one arm, drawing movements of 2-D patterns, and tennis swings. Our results demonstrate (a) that multi-joint human movements can be encoded successfully by the CPs, (b) that a learned movement policy can readily be reused to produce robust trajectories towards different targets, (c) that a policy fitted for one particular target provides a good predictor of human reaching movements towards neighboring targets, and (d) that the parameter space which encodes a policy is suitable for measuring to which extent two trajectories are qualitatively similar.

> 70,000) derived from six representative model organisms (human, mouse, rat, fruit fly, nematode, and budding yeast), and have devised a data-mining platform-designated ChIP-Atlas (http://chip-atlas.org). ChIP-Atlas is able to show alignment and peak-call results for all public ChIP-seq and DNase-seq data archived in the NCBI Sequence Read Archive (SRA), which encompasses data derived from GEO, ArrayExpress, DDBJ, ENCODE, Roadmap Epigenomics, and the scientific literature. All peak-call data are integrated to visualize multiple histone modifications and binding sites of transcriptional regulators (TRs) at given genomic loci. The integrated data can be further analyzed to show TR-gene and TR-TR interactions, as well as to examine enrichment of protein binding for given multiple genomic coordinates or gene names. ChIP-Atlas is superior to other platforms in terms of data number and functionality for data mining across thousands of ChIP-seq experiments, and it provides insight into gene regulatory networks and epigenetic mechanisms.

The ProteomeXchange (PX) consortium of proteomics resources (http://www.proteomexchange.org) has standardized data submission and dissemination of mass spectrometry proteomics data worldwide since 2012. In this paper, we describe the main developments since the previous update manuscript was published in Nucleic Acids Research in 2017. Since then, in addition to the four PX existing members at the time (PRIDE, PeptideAtlas including the PASSEL resource, MassIVE and jPOST), two new resources have joined PX: iProX (China) and Panorama Public (USA). We first describe the updated submission guidelines, now expanded to include six members. Next, with current data submission statistics, we demonstrate that the proteomics field is now actively embracing public open data policies. At the end of June 2019, more than 14 100 datasets had been submitted to PX resources since 2012, and from those, more than 9 500 in just the last three years. In parallel, an unprecedented increase of data re-use activities in the field, including 'big data' approaches, is enabling novel research and new data resources. At last, we also outline some of our future plans for the coming years.

Studying the role of essential proteins is dependent upon a method for rapid inactivation, in order to study the immediate phenotypic consequences. Auxin-inducible degron (AID) technology allows rapid depletion of proteins in animal cells and fungi, but its application to human cells has been limited by the difficulties of tagging endogenous proteins. We have developed a simple and scalable CRISPR/Cas-based method to tag endogenous proteins in human HCT116 and mouse embryonic stem (ES) cells by using donor constructs that harbor synthetic short homology arms. Using a combination of AID tagging with CRISPR/Cas, we have generated conditional alleles of essential nuclear and cytoplasmic proteins in HCT116 cells, which can then be depleted very rapidly after the addition of auxin to the culture medium. This approach should greatly facilitate the functional analysis of essential proteins, particularly those of previously unknown function.

In this paper we discuss augmented reality (AR) displays in a general sense, within the context of a reality-virtuality (RV) continuum, encompassing a large class of `mixed reality' (MR) displays, which also includes augmented virtuality (AV). MR displays are defined by means of seven examples of existing display concepts in which real objects and virtual objects are juxtaposed. Essential factors which distinguish different MR display systems from each other are presented, first by means of a table in which the nature of the underlying scene, how it is viewed, and the observer's reference to it are compared, and then by means of a three dimensional taxonomic framework comprising: extent of world knowledge, reproduction fidelity, and extent of presence metaphor. A principal objective of the taxonomy is to clarify terminology issues and to provide a framework for classifying research across different disciplines.

Major advancements have recently been made in mass spectrometry-based proteomics, yielding an increasing number of datasets from various proteomics projects worldwide. In order to facilitate the sharing and reuse of promising datasets, it is important to construct appropriate, high-quality public data repositories. jPOSTrepo (https://repository.jpostdb.org/) has successfully implemented several unique features, including high-speed file uploading, flexible file management and easy-to-use interfaces. This repository has been launched as a public repository containing various proteomic datasets and is available for researchers worldwide. In addition, our repository has joined the ProteomeXchange consortium, which includes the most popular public repositories such as PRIDE in Europe for MS/MS datasets and PASSEL for SRM datasets in the USA. Later MassIVE was introduced in the USA and accepted into the ProteomeXchange, as was our repository in July 2016, providing important datasets from Asia/Oceania. Accordingly, this repository thus contributes to a global alliance to share and store all datasets from a wide variety of proteomics experiments. Thus, the repository is expected to become a major repository, particularly for data collected in the Asia/Oceania region.