Andreas Bueckle
A5019197163- Single-cell and spatial transcriptomics
- Health, Environment, Cognitive Aging
- AI in cancer detection
- Biomedical Text Mining and Ontologies
- Medical Imaging Techniques and Applications
- Cell Image Analysis Techniques
- Cancer Genomics and Diagnostics
- Anatomy and Medical Technology
- Augmented Reality Applications
- 3D Shape Modeling and Analysis
- Data Visualization and Analytics
- Medical Image Segmentation Techniques
- Surgical Simulation and Training
- Bioinformatics and Genomic Networks
- Human Pose and Action Recognition
- Stroke Rehabilitation and Recovery
- Computer Graphics and Visualization Techniques
- Chronic Kidney Disease and Diabetes
- Radiomics and Machine Learning in Medical Imaging
- Geographic Information Systems Studies
- Genetics, Aging, and Longevity in Model Organisms
- Semantic Web and Ontologies
- Lipid metabolism and disorders
- Renal and related cancers
- Image Retrieval and Classification Techniques
Indiana University Bloomington
2018-2025
Indiana University
2021-2024
National Institute of Allergy and Infectious Diseases
2022
National Institutes of Health
2022
Intelligent Systems Research (United States)
2022
In the information age, ability to read and construct data visualizations becomes as important write text. However, while standard definitions theoretical frameworks teach assess textual, mathematical, visual literacy exist, current visualization (DVL) are not comprehensive enough guide design of DVL teaching assessment. This paper introduces a framework (DVL-FW) that was specifically developed define, teach, DVL. The holistic DVL-FW promotes both reading construction visualizations, pairing...
Abstract Background Image-based machine learning tools hold great promise for clinical applications in pathology research. However, the ideal end-users of these computational (e.g., pathologists and biological scientists) often lack programming experience required setup use which rely on command line interfaces. Methods We have developed Histo-Cloud , a tool segmentation whole slide images (WSIs) that has an easy-to-use graphical user interface. This runs state-of-the-art convolutional...
The Human BioMolecular Atlas Program (HuBMAP) aims to construct a reference 3D structural, cellular, and molecular atlas of the healthy adult human body. HuBMAP Data Portal (https://portal.hubmapconsortium.org) serves experimental datasets supports data processing, search, filtering, visualization. Reference (HRA) (https://humanatlas.io) provides open access data, code, procedures, instructional materials. Experts from more than 20 consortia are collaborating HRA's Common Coordinate...
The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in healthy human body. It compiled by an international team experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. third HRA release (v1.2) covers spatial data and ontology annotations for 26 organs. Experts access via spreadsheets view object models editing tools. This paper introduces Common Coordinate Framework (CCF)...
Abstract The aging process is universal, and it characterized by a progressive deterioration decrease in physiological function leading to decline on the organismal level. Nevertheless, number of genetic non-genetic interventions have been described, which successfully extend healthspan lifespan different species. Furthermore, clinical trials evaluating feasibility promote human health. goal annual Biological Sciences Section Gerontological Society America meeting was share current knowledge...
Abstract Background The advancement of single cell technologies has driven significant progress in constructing a multiscale, pan-organ Human Reference Atlas (HRA) for healthy human cells, though challenges remain harmonizing types and unifying nomenclature. Multiple machine learning artificial intelligence methods, including pre-trained fine-tuned models on large-scale atlas data, are publicly available the community users to computationally annotate match their clusters reference atlas....
Abstract The Human BioMolecular Atlas Program (HuBMAP) aims to compile a Reference (HRA) for the healthy adult body at cellular level. Functional tissue units (FTUs), relevant HRA construction, are of pathobiological significance. Manual segmentation FTUs does not scale; highly accurate and performant, open-source machine-learning algorithms needed. We designed hosted Kaggle competition that focused on development such 1200 teams from 60 countries participated. present outcomes an expanded...
Working with organs and extracted tissue blocks is an essential task in many medical surgery anatomy environments. In order to prepare specimens from human donors for further analysis, wet-bench workers must properly dissect collect metadata downstream including information about the spatial origin of tissue. The Registration User Interface (RUI) was developed allow stakeholders Human Biomolecular Atlas Program (HuBMAP) register blocks—i.e., record size, position, orientation data regard...
Seventeen international consortia are collaborating on a human reference atlas (HRA), comprehensive, high-resolution, three-dimensional of all the cells in healthy body. Laboratories around world collecting tissue specimens from donors varying sex, age, ethnicity, and body mass index. However, harmonizing data across 25 organs more than 15 bulk spatial single-cell assay types poses challenges. Here, we present software tools user interfaces developed to spatially semantically annotate...
Diabetic kidney disease (DKD) is the leading cause of end-stage (ESKD). Prognostic biomarkers reflective underlying molecular mechanisms are critically needed for effective management DKD. A three-marker panel was derived from a proteomics analysis plasma samples by an unbiased machine learning approach participants (N = 58) in Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this improved prediction composite outcome ESKD or 40% decline...
The Human Reference Atlas (HRA, https://humanatlas.io) funded by the NIH Biomolecular Program (HuBMAP, https://commonfund.nih.gov/hubmap) and other projects engages 17 international consortia to create a spatial reference of healthy adult human body at single-cell resolution. specimen, biological structure, data that define HRA are disparate in nature benefit from visually explicit method integration. Virtual reality (VR) offers unique means enable users explore complex structures...
The human body is made up of about 37 trillion cells (adults). Each cell has its own unique role and affected by neighboring environment. NIH Human BioMolecular Atlas Program (HuBMAP) aims at developing a 3D atlas consisting organs, vessels, tissues to singe with all spatially registered in single using obtained from normal individuals across wide range ages. A critical step building the register tissue blocks real-time right location organ, which itself consists complex sub-structures....
1. Abstract This paper reviews efforts across 16 international consortia to construct human anatomical structures, cell types, and biomarkers (ASCT+B) tables three-dimensional reference organs in support of a Human Reference Atlas. We detail the ontological descriptions spatial representations together with user interfaces that registration exploration tissue data. Four use cases are presented demonstrate utility ASCT+B for advancing biomedical research improving health.
Virtual reality (VR) has seen increased use for training and instruction. Designers can enable VR users to gain insights into their own performance by visualizing telemetry data from actions in VR. Our ability detect patterns trends visually suggests the of visualization as a tool identify strategies improved performance. Typical tasks scenarios are manipulation 3D objects (e.g., learning how maintain jet engine) navigation learn geography building or landscape before traveling on-site). In...
Abstract Several international consortia are collaborating to construct a human reference atlas, which is comprehensive, high-resolution, three-dimensional atlas of all the cells in healthy body. Laboratories around world collecting tissue specimens from donors varying sex, age, ethnicity, and body mass index. However, integrating harmonizing data across 20+ organs more than 15 bulk spatial single-cell assay types poses diverse challenges. Here we present software tools user interfaces...
Abstract The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in healthy human body. It compiled by an international team experts that develop standard terminologies linked to 3D reference objects describing anatomical structures. third HRA release (v1.2) covers spatial data and ontology annotations for 26 organs. Experts access via spreadsheets view models editing tools. This paper introduces Common Coordinate Framework Ontology (CCFO)...
Abstract The Human Reference Atlas (HRA) for the healthy, adult body is developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures describing specimens, biological structures, spatial positions experimental datasets ontology-linked reference anatomical (AS), cell types (CT), biomarkers (B). We introduce HRA Knowledge Graph (KG) as central resource v2.2, supporting cross-scale, queries to Resource Description...
The Human Reference Atlas (HRA, https://humanatlas.io ) funded by the NIH Biomolecular Program (HuBMAP, https://commonfund.nih.gov/hubmap and other projects engages 17 international consortia to create a spatial reference of healthy adult human body at single-cell resolution. specimen, biological structure, data that define HRA are disparate in nature benefit from visually explicit method integration. Virtual reality (VR) offers unique means enable users explore complex structures...
Abstract The Human BioMolecular Atlas Program aims to compile a reference atlas for the healthy human adult body at cellular level. Functional tissue units (FTU, e.g., renal glomeruli and colonic crypts) are of pathobiological significance relevant modeling understanding disease progression. Yet, annotation FTUs is time consuming expensive when done manually existing algorithms achieve low accuracy do not generalize well. This paper compares five winning from “Hacking Kidney” Kaggle...