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3D Brain Atlas Reconstructor Service-Online repository of Three-Dimensional Models of Brain Structures

NEUROINFORMATICS 2013年第4期11卷 507-518页

作者： Majka, Piotr Kowalski, Jakub M. Chlodzinska, Natalia Wojcik, Daniel K. Nencki Inst Expt Biol PL-02093 Warsaw Poland

Brain atlases are important tools of neuroscience. Traditionally prepared in paper book format, more and more commonly they take digital form which extends their utility. To simplify work with different atlases, to lay the ground for developing universal tools which could abstract from the origin of the atlas, efforts are being made to provide common interfaces to these atlases. 3D Brain Atlas Reconstructor service (3dBARs) described here is a repository of digital representations of different brain atlases in CAF format which we recently proposed and a repository of 3D models of brain structures. A graphical front-end is provided for creating and viewing the reconstructed models as well as the underlying 2D atlas data. An application programming interface (API) facilitates programmatic access to the service contents from other websites. From a typical user's point of view, 3dBARs offers an accessible way to mine publicly available atlasing data with a convenient browser based interface, without the need to install extra software. For a developer of services related to brain atlases, 3dBARs supplies mechanisms for enhancing functionality of other software. The policy of the service is to accept new datasets as delivered by interested parties and we work with the researchers who obtain original data to make them available to the neuroscience community at large. The functionality offered by the 3dBARs situates it at the core of present and future general atlasing services tying it strongly to the global atlasing neuroinformatics infrastructure.

关键词： Web service data repository Reproducible research Brain atlas Tool interoperability 3D visualization WebGL 3D reconstruction Visualization

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Open Science CBS Neuroimaging repository: Sharing ultra-high-field MR images of the brain

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NEUROIMAGE 2016年第PT B期124卷 1143-1148页

作者： Tardif, Christine Lucas Schaefer, Andreas Trampel, Robert Villringer, Arno Turner, Robert Bazin, Pierre-Louis Max Planck Inst Human Cognit & Brain Sci Dept Neurol D-04103 Leipzig Germany Max Planck Inst Human Cognit & Brain Sci Dept Neurophys D-04103 Leipzig Germany

Magnetic resonance imaging at ultra high field opens the door to quantitative brain imaging at sub-millimeter isotropic resolutions. However, novel image processing tools to analyze these new rich datasets are lacking. In this article, we introduce the Open Science CBS Neuroimaging repository: a unique repository of high-resolution and quantitative images acquired at 7 T. The motivation for this project is to increase interest for high-resolution and quantitative imaging and stimulate the development of image processing tools developed specifically for high-field data. Our growing repository currently includes datasets from MP2RAGE and multi-echo FLASH sequences from 28 and 20 healthy subjects respectively. These datasets represent the current state-of-the-art in in-vivo relaxometry at 7 T, and are now fully available to the entire neuroimaging community. (C) 2015 Elsevier Inc. All rights reserved.

关键词： data repository Ultra-high field Magnetic resonance imaging Quantitative imaging High-resolution imaging Relaxometry

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Recent Advances in Pathology: the 2022 Annual Review Issue of The Journal of Pathology

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JOURNAL OF PATHOLOGY 2022年第4期257卷 379-382页

作者： Herrington, C. Simon Poulsom, Richard Pillay, Nischalan Bankhead, Peter Coates, Philip J. Univ Edinburgh Inst Genet & Canc Edinburgh Canc Res Ctr Edinburgh Midlothian Scotland Univ Edinburgh Edinburgh Pathol Inst Genet & Canc Edinburgh Midlothian Scotland Pathol Soc Great Britain & Ireland London England UCL Canc Inst Sarcoma Biol & Genom Grp London England Royal Natl Orthopaed Hosp NHS Trust Dept Histopathol London England Univ Edinburgh Inst Genet & Canc Ctr Genom Expt Med Edinburgh Midlothian Scotland Masaryk Mem Canc Inst RECAMO Brno Czech Republic

The 2022 Annual Review Issue of The Journal of Pathology, Recent Advances in Pathology, contains 15 invited reviews on research areas of growing importance in pathology. This year, the articles include those that focus on digital pathology, employing modern imaging techniques and software to enable improved diagnostic and research applications to study human diseases. This subject area includes the ability to identify specific genetic alterations through the morphological changes they induce, as well as integrating digital and computational pathology with 'omics technologies. Other reviews in this issue include an updated evaluation of mutational patterns (mutation signatures) in cancer, the applications of lineage tracing in human tissues, and single cell sequencing technologies to uncover tumour evolution and tumour heterogeneity. The tissue microenvironment is covered in reviews specifically dealing with proteolytic control of epidermal differentiation, cancer-associated fibroblasts, field cancerisation, and host factors that determine tumour immunity. All of the reviews contained in this issue are the work of invited experts selected to discuss the considerable recent progress in their respective fields and are freely available online (https://***/journal/10969896). (C) 2022 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

关键词： 3D reconstruction adult stem cells artificial intelligence asthma biomarkers breast cancer cancer cancer-adjacent tissues cancer-associated fibroblasts chromothripsis chronic obstructive pulmonary disease clonal dynamics clonality analysis colon computational pathology convolutional neural networks copy number aberrations copy number signatures cystic fibrosis data repository desquamation digital pathology DNA sequencing epidermal inflammation epidermis epithelial transition states extrachromosomal DNA field cancerisation filaggrin functional pathology genomics haemopoietic stem cells host idiopathic pulmonary fibrosis image analysis image processing immune checkpoint inhibitors immune system immunotherapy in situ hybridisation intestinal stem cells intra-tumour heterogeneity in vivo models kallikrein-related peptidases lineage tracing lung atlas lung diseases lung progenitors lung stem cells machine learning metabolome microbiome mutational signatures open science PAR1 PAR2 patient stratification prediction prognosis protease inhibitors proteolytic cascades quantitative methods QuPath single cell DNA sequencing single cell RNA sequencing single cell transcriptomics skin diseases skin physiology software structural variants subclone tumour evolution tumour phylogeny virtual slide whole-slide imaging whole-slide scanning whole genome sequencing

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Interactive webtool for analyzing drug sensitivity and resistance associated with genetic signatures of cancer cell lines

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JOURNAL OF CANCER RESEARCH AND CLINICAL ONCOLOGY 2023年第9期149卷 5539-5545页

作者： Boeschen, Myriam Le Duc, Diana Stiller, Mathias von Laffert, Maximilian Schoeneberg, Torsten Horn, Susanne Univ Leipzig Med Fac Rudolf Schonheimer Inst Biochem Johannisallee 30 D-04103 Leipzig Germany Univ Leipzig Inst Human Genet Med Ctr Leipzig Germany Univ Hosp Leipzig Inst Pathol Leipzig Germany Univ Duisburg Essen Univ Hosp Essen Dept Dermatol D-45122 Essen Germany German Canc Consortium DKTK Partner Site Essen Dusseldorf D-45122 Essen Germany

Purpose A wide therapeutic repertoire has become available to oncologists including radio-and chemotherapy, small molecules and monoclonal antibodies. However, drug efficacy can be limited by genetic heterogeneity. Here, we designed a webtool that facilitates the data analysis of the in vitro drug sensitivity data on 265 approved compounds from the GDSC database in association with a plethora of genetic changes documented for 1001 cell lines in the CCLE data. Methods The webtool computes odds ratios of drug resistance for a queried set of genetic alterations. It provides results on the efficacy of single compounds or groups of compounds assigned to cellular signaling pathways. Webtool availability: https://***/GDSC/. Results We first replicated established associations of genetic driver mutations in BRAF, RAS genes and EGFR with drug response. We then tested the "BRCAness' hypothesis and did not find increased sensitivity to the assayed PARP inhibitors. Analyzing specific PIK3CA mutations related to cancer and mendelian overgrowth, we found support for the described sensitivity of H1047 mutants to GSK690693 targeting the AKT pathway. Testing a co-mutated gene pair, GATA3 activation abolished PTEN-related sensitivity to PI3K/mTOR inhibition. Finally, the pharmacogenomic modifier ABCB1 was associated with olaparib resistance. Conclusions This tool could identify potential drug candidates in the presence of custom sets of genetic changes and moreover, improve the understanding of signaling pathways. The underlying computer code can be adapted to larger drug response datasets to help structure and accommodate the increasingly large biomedical knowledge base.

关键词： Association test Candidate compound data repository Discovery approach

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Easily configured real-time CPOE Pick Off Tool supporting focused clinical research and quality improvement

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JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION 2014年第3期21卷 564-+页

作者： Rosenbaum, Benjamin P. Silkin, Nikolay Miller, Randolph A. Vanderbilt Univ Med Ctr Dept Biomed Informat Nashville TN 37232 USA Oregon Hlth & Sci Univ Dept Med Informat & Clin Epidemiol Portland OR 97201 USA Cleveland Clin Neurol Inst Dept Neurosurg Cleveland OH 44106 USA Principal Financial Grp Des Moines IA USA

Real-time alerting systems typically warn providers about abnormal laboratory results or medication interactions. For more complex tasks, institutions create site-wide 'data warehouses' to support quality audits and longitudinal research. Sophisticated systems like i2b2 or Stanford's STRIDE utilize data warehouses to identify cohorts for research and quality monitoring. However, substantial resources are required to install and maintain such systems. For more modest goals, an organization desiring merely to identify patients with 'isolation' orders, or to determine patients' eligibility for clinical trials, may adopt a simpler, limited approach based on processing the output of one clinical system, and not a data warehouse. We describe a limited, order-entry-based, real-time 'pick off' tool, utilizing public domain software (PHP, MySQL). Through a web interface the tool assists users in constructing complex order-related queries and auto-generates corresponding database queries that can be executed at recurring intervals. We describe successful application of the tool for research and quality monitoring.

关键词： data repository data Warehouse EMR Pick Off Tool Pickoff

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Dana-Farber repository for machine learning in immunology

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JOURNAL OF IMMUNOLOGICAL METHODS 2011年第1-2期374卷 18-25页

作者： Zhang, Guang Lan Lin, Hong Huang Keskin, Derin B. Reinherz, Ellis L. Brusic, Vladimir Dana Farber Canc Inst Canc Vaccine Ctr Boston MA 02115 USA

The immune system is characterized by high combinatorial complexity that necessitates the use of specialized computational tools for analysis of immunological data. Machine learning (ML) algorithms are used in combination with classical experimentation for the selection of vaccine targets and in computational simulations that reduce the number of necessary experiments. The development of ML algorithms requires standardized data sets, consistent measurement methods, and uniform scales. To bridge the gap between the immunology community and the ML community, we designed a repository for machine learning in immunology named Dana-Farber repository for Machine Learning in Immunology (DFRMLI). This repository provides standardized data sets of HLA-binding peptides with all binding affinities mapped onto a common scale. It also provides a list of experimentally validated naturally processed T cell epitopes derived from tumor or virus antigens. The DFRMLI data were preprocessed and ensure consistency, comparability, detailed descriptions, and statistically meaningful sample sizes for peptides that bind to various HLA molecules. The repository is accessible at http://***/DFRMLI/. (C) 2011 Elsevier B.V. All rights reserved.

关键词： HLA binding Prediction Mathematical model data repository Immune system T cell epitope

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AusGeochem: An Open Platform for Geochemical data Preservation, Dissemination and Synthesis

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GEOSTANDARDS AND GEOANALYTICAL RESEARCH 2022年第2期46卷 245-259页

作者： Boone, Samuel C. Dalton, Hayden Prent, Alexander Kohlmann, Fabian Theile, Moritz Greau, Yoann Florin, Guillaume Noble, Wayne Hodgekiss, Sally-Ann Ware, Bryant Phillips, David Kohn, Barry O'Reilly, Suzanne Gleadow, Andrew McInnes, Brent Rawling, Tim Univ Melbourne Sch Geog Earth & Atmospher Sci Melbourne Vic 3010 Australia Curtin Univ John de Laeter Ctr Bentley WA 6102 Australia Lithodat Pty Ltd Melbourne Vic 3030 Australia Macquarie Univ Dept Earth & Environm Sci Sydney NSW 2109 Australia Univ Melbourne AuScope Melbourne Vic 3010 Australia

To promote a more efficient and transparent geochemistry data ecosystem, a consortium of Australian university research laboratories called the AuScope Geochemistry Network assembled to build a collaborative platform for the express purpose of preserving, disseminating and collating geochronology and isotopic data. In partnership with geoscience-data-solutions company Lithodat Pty Ltd, the open, cloud-based AusGeochem platform () was developed to simultaneously serve as a geosample registry, a geochemical data repository and a data analysis tool. Informed by method-specific groups of geochemistry experts and established international data reporting practices, community-agreed database schemas were developed for rock and mineral geosample metadata and secondary ion mass spectrometry U-Pb analysis, with additional models for laser ablation-inductively coupled-mass spectrometry U-Pb and Lu-Hf, Ar-Ar, fission-track and (U-Th-Sm)/He under development. Collectively, the AusGeochem platform provides the geochemistry community with a new, dynamic resource to help facilitate FAIR (Findable, Accessible, Interoperable, Reusable) data management, streamline data dissemination and advanced quantitative investigations of Earth system processes. By systematically archiving detailed geochemical (meta-)data in structured schemas, intractably large datasets comprising thousands of analyses produced by numerous laboratories can be readily interrogated in novel and powerful ways. These include rapid derivation of inter-data relationships, facilitating on-the-fly data compilation, analysis and visualisation.

关键词： geochemical data platform geosample registry data repository Big data FAIR data

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PMLB: a large benchmark suite for machine learning evaluation and comparison

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BIOdata MINING 2017年第1期10卷 1-13页

作者： Olson, Randal S. La Cava, William Orzechowski, Patryk Urbanowicz, Ryan J. Moore, Jason H. Univ Penn Inst Biomed Informat 3700 Hamilton Walk Philadelphia PA 19104 USA AGH Univ Sci & Technol Dept Automat & Biomed Engn Krakow Poland

Background: The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. Results: The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. From this study, we find that existing benchmarks lack the diversity to properly benchmark machine learning algorithms, and there are several gaps in benchmarking problems that still need to be considered. Conclusions: This work represents another important step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.

关键词： Machine learning Model evaluation Benchmarking data repository

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The elegant machine: Applying technology to optimize clinical trials

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DRUG INFORMATION JOURNAL 1998年第4期32卷 861-869页

作者： Kubick, WR PAREXEL Int Corp Informat Technol Waltham MA 02154 USA

A new model for conducting clinical research programs in the future is beginning to evolve which will emphasize collaboration, interdependency, and close interactive sharing of information among the various stakeholders in the research process: patient investigator;sponsor project manager medical monitor data management organization, laboratories, biostatisticians, and regulatory authorities. This model will conserve the use of information by minimizing redundancies, transcriptions, and data conversions in a continuous dataflow, simplifying the data clarification process, and using the "best fit" technology tool for capturing and accessing clinical information. This View of clinical research will be based on a generic data repository based upon evolving International Conference on Harmonization/Food and Drug Administration (ICH/FDA) data standards which will also support trials management and safety monitoring with respect to the data repository The current state of alternative data capture technologies such as interactive voice response systems (IVRS), remote data entry (RDE), image recognition, Internet technologies, hand-held computers, voice recognition, and wearable monitoring devices will be reviewed.

关键词： data management electronic data capture (EDC) optical imaging interactive voice response (IVR) data repository

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The pharmacokinetic/pharmacodynamic research tool (PRESTO):: An advanced concept for rational drug development

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DRUG INFORMATION JOURNAL 2002年第1期36卷 57-66页

作者： Göller, G Mück, W Koss, D Nörtersheuser, P Osswald, M Kovar, A Zurth, C Poland, H Bayer AG PH PD P Preclin Pharmacokinet D-42096 Wuppertal Germany Asta Med AG Frankfurt Germany Abbott GmbH & Co KG Wiesbaden Germany Boehringer Ingelheim Pharma KG Biberach Germany Merck KGaA Darmstadt Germany Schering AG D-1000 Berlin Germany

In Germany in 1995 an intercompany expert working group was formed to define a flexible structure for a modern database system, named the Pharmacokinetic/Pharmacodynamic RESearch TOol (PRESTO), which handles pharmacokinetic/pharmacodynamic (PK/PD) results of entire research and development (R&D) projects, thus going beyond the information available in laboratory or clinical data systems generally present in most companies. PRESTO consists of two main modules: a database and an analysis system. The database part of PRESTO is designed for storing and managing PK and PD study data. Associated information such as biochemistry, toxicokinetic, physico-chemistry, and clinical chemistry data can also be handled to aid the interpretation of results, if necessary. The database will be used as a source for all kinds of pharmacokinetic, pharmacodynamic, and biometric evaluations. The extraction of data across studies to prepare meta-analyses is an essential feature of this system. The analysis system part of PRESTO provides uniform graphical interfaces to the database and to commercially available and proprietary data analysis programs (noncompartmental, compartmental PK, effect modeling, population PK/PD) as well as statistical software packages. The database part is then additionally used as a repository of the results from these evaluations. PRESTO is designed to a modular concept and a flexible data model, and offers configuration to site-specific needs. The concept supports fulfillment of Good Clinical Practice/Good Laboratory Practice requirements.

关键词： pharmacokinetics pharmacodynamics data analysis data repository data management

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