
Over 20 months, contributed to RBVI/ChimeraX by building and refining scientific software for protein structure prediction, visualization, and analysis. Developed features such as Boltz and OpenFold integration, mutation scoring heatmaps, and advanced 3D/VR display support, focusing on robust data handling and user-centric UI enhancements. Addressed cross-platform deployment, GPU optimization, and backend reliability using Python, C++, and Qt, while improving workflows for AlphaFold, ColabFold, and batch ligand predictions. Maintained high code quality through targeted bug fixes, documentation, and error handling. Work in the RBVI/ChimeraX repository enabled scalable, reproducible research and streamlined complex bioinformatics and cheminformatics pipelines.
June 2026 monthly summary for RBVI/ChimeraX focusing on key deliverables and stability improvements. Primary work centered on GUI robustness for color mapping and label/arrow interactions, along with enabling clearer user guidance through documentation.
June 2026 monthly summary for RBVI/ChimeraX focusing on key deliverables and stability improvements. Primary work centered on GUI robustness for color mapping and label/arrow interactions, along with enabling clearer user guidance through documentation.
May 2026 (RBVI/ChimeraX) delivered targeted GPU/Colab integration, UX- and analytics-enhancing mutations heatmap features, robust data association, and stability fixes across macOS. These efforts reduce setup friction, accelerate insight generation, and improve reliability for scientists relying on ChimeraX for structure analysis and mutation impact interpretation.
May 2026 (RBVI/ChimeraX) delivered targeted GPU/Colab integration, UX- and analytics-enhancing mutations heatmap features, robust data association, and stability fixes across macOS. These efforts reduce setup friction, accelerate insight generation, and improve reliability for scientists relying on ChimeraX for structure analysis and mutation impact interpretation.
In April 2026, the RBVI/ChimeraX team delivered targeted feature enhancements and reliability fixes around mutation scoring, heatmaps, and data integration, while expanding OpenFold capabilities. Notable work includes a capped auto-radius for cartoon helix rendering, a GUI for named mutation score ranges, comprehensive mutation score heatmap improvements with configurability and persistent state, and multi-seed support for OpenFold predictions. We also extended data ingestion with MaveDB-compatible mutation CSV reading and UniProt population frequency extraction, enabling richer downstream analyses. These changes collectively improve visualization fidelity, data accuracy, and end-to-end workflow efficiency for mutation analysis and visualization.
In April 2026, the RBVI/ChimeraX team delivered targeted feature enhancements and reliability fixes around mutation scoring, heatmaps, and data integration, while expanding OpenFold capabilities. Notable work includes a capped auto-radius for cartoon helix rendering, a GUI for named mutation score ranges, comprehensive mutation score heatmap improvements with configurability and persistent state, and multi-seed support for OpenFold predictions. We also extended data ingestion with MaveDB-compatible mutation CSV reading and UniProt population frequency extraction, enabling richer downstream analyses. These changes collectively improve visualization fidelity, data accuracy, and end-to-end workflow efficiency for mutation analysis and visualization.
March 2026 (2026-03) monthly summary for RBVI/ChimeraX focused on delivering high-value reliability improvements, performance optimizations, and expanded XR3D capabilities. The team stabilized core data flows, accelerated visualization interactions, and extended display options, enabling faster exploration and more robust deployment of ChimeraX features. Business impact includes more reliable Alphafold data retrieval, faster mutation analysis loops for researchers, and richer 3D visualization workflows for XR-enabled setups.
March 2026 (2026-03) monthly summary for RBVI/ChimeraX focused on delivering high-value reliability improvements, performance optimizations, and expanded XR3D capabilities. The team stabilized core data flows, accelerated visualization interactions, and extended display options, enabling faster exploration and more robust deployment of ChimeraX features. Business impact includes more reliable Alphafold data retrieval, faster mutation analysis loops for researchers, and richer 3D visualization workflows for XR-enabled setups.
February 2026 — RBVI/ChimeraX monthly summary: Delivered significant features, reliability improvements, and cross-platform deployment enhancements that increase scientific productivity and user experience. Notable work includes Mutation Score Visualization Enhancements, OpenFold deployment improvements (CPU-based predictions, remote execution, Windows path handling), isoform handling fixes for AlphaFold and FoldSeek, daily build integration and branch updates, and comprehensive OpenFold batch ligand enhancements. Documentation cleanup and accessibility updates improve maintainability and onboarding.
February 2026 — RBVI/ChimeraX monthly summary: Delivered significant features, reliability improvements, and cross-platform deployment enhancements that increase scientific productivity and user experience. Notable work includes Mutation Score Visualization Enhancements, OpenFold deployment improvements (CPU-based predictions, remote execution, Windows path handling), isoform handling fixes for AlphaFold and FoldSeek, daily build integration and branch updates, and comprehensive OpenFold batch ligand enhancements. Documentation cleanup and accessibility updates improve maintainability and onboarding.
January 2026 monthly summary for RBVI/ChimeraX highlighting reliability, deployment, and integration improvements that enable faster and more robust Boltz-based workflows, stronger visualization fidelity, and clearer documentation. Emphasis on business value through improved deployment accessibility, cross-platform log consistency, and open-fold integration.
January 2026 monthly summary for RBVI/ChimeraX highlighting reliability, deployment, and integration improvements that enable faster and more robust Boltz-based workflows, stronger visualization fidelity, and clearer documentation. Emphasis on business value through improved deployment accessibility, cross-platform log consistency, and open-fold integration.
December 2025: Stabilized AI-assisted workflows in ChimeraX with cross-platform MCP reliability, expanded Boltz server capabilities for scalable predictions, and improved onboarding through documentation and UI improvements. Delivered new configuration tooling for Claude Desktop, Claude AI integration tweaks, and NotebookLM help, along with a suite of bug fixes that reduce noise and improve stability across Windows, Mac, and Linux environments. Result: faster, more reliable AI-assisted workflows, clearer error handling, and better observability for operations and users.
December 2025: Stabilized AI-assisted workflows in ChimeraX with cross-platform MCP reliability, expanded Boltz server capabilities for scalable predictions, and improved onboarding through documentation and UI improvements. Delivered new configuration tooling for Claude Desktop, Claude AI integration tweaks, and NotebookLM help, along with a suite of bug fixes that reduce noise and improve stability across Windows, Mac, and Linux environments. Result: faster, more reliable AI-assisted workflows, clearer error handling, and better observability for operations and users.
Month: 2025-11 — In RBVI/ChimeraX, focused on improving reliability of the Boltz Predict workflow by fixing absolute path handling for the resultsDirectory option. This change ensures that absolute paths are correctly recognized and used, preventing errors during predictions and improving reproducibility in automated pipelines.
Month: 2025-11 — In RBVI/ChimeraX, focused on improving reliability of the Boltz Predict workflow by fixing absolute path handling for the resultsDirectory option. This change ensures that absolute paths are correctly recognized and used, preventing errors during predictions and improving reproducibility in automated pipelines.
2025-10 monthly performance summary for RBVI/ChimeraX. This period emphasized stability, data integrity, and user experience improvements across Boltz/Alphafold integration, mutation scores visualization, 2D labeling UI, and cross-platform robustness. Delivered targeted bug fixes, new GUI enhancements, and sequence-alignment improvements that boost reliability, reproducibility, and developer/productivity.
2025-10 monthly performance summary for RBVI/ChimeraX. This period emphasized stability, data integrity, and user experience improvements across Boltz/Alphafold integration, mutation scores visualization, 2D labeling UI, and cross-platform robustness. Delivered targeted bug fixes, new GUI enhancements, and sequence-alignment improvements that boost reliability, reproducibility, and developer/productivity.
September 2025 monthly performance summary for RBVI/ChimeraX focused on delivering higher automation for protein prediction workflows, improving reliability, and expanding data integration and accessibility. The team delivered significant AlphaFold workflow enhancements, bolstered Boltz robustness and simplified installation, expanded documentation for resource access, and strengthened mmcif/EMDB integration. These changes reduce setup time, improve prediction throughput, and enhance data interoperability with external resources.
September 2025 monthly performance summary for RBVI/ChimeraX focused on delivering higher automation for protein prediction workflows, improving reliability, and expanding data integration and accessibility. The team delivered significant AlphaFold workflow enhancements, bolstered Boltz robustness and simplified installation, expanded documentation for resource access, and strengthened mmcif/EMDB integration. These changes reduce setup time, improve prediction throughput, and enhance data interoperability with external resources.
August 2025 RBVI/ChimeraX: Delivered scalable Boltz batch ligand predictions through a new BoltzPrediction framework, stabilized batch workflows, and enhanced integration and documentation to accelerate onboarding and reproducible results. Implemented default installation path to ~/boltz22, export of CSV results, and user-facing UI improvements, while addressing platform-specific stability and TensorFlow-related issues. The work reduces manual intervention, improves throughput for ligand screening, and strengthens reliability of Boltz batch predictions across workflows.
August 2025 RBVI/ChimeraX: Delivered scalable Boltz batch ligand predictions through a new BoltzPrediction framework, stabilized batch workflows, and enhanced integration and documentation to accelerate onboarding and reproducible results. Implemented default installation path to ~/boltz22, export of CSV results, and user-facing UI improvements, while addressing platform-specific stability and TensorFlow-related issues. The work reduces manual intervention, improves throughput for ligand screening, and strengthens reliability of Boltz batch predictions across workflows.
Monthly summary for 2025-07: Key features delivered: - Boltz 2 migration completed across Mac/Linux runtimes with affinity prediction; updated UI entries and improved error messaging for Boltz predictions. Includes new runtimes (Mac 16GB/32GB, Linux 64-bit) and per-ligand entries in the affinity menu. - OpenXR 3D display enhancements expanded to Acer SpatialLabs with reliable "xr on" activation; added mouse tracking and input support for Sony and Acer 3D displays; implemented atom and residue labels on hover. - Improved maintainability and UX: refactored mouse hover logic to decouple hover detection from the hover module, improving code organization and reliability. - Stability and data handling improvements: fixes for opening 2D TIFF stacks; surface color mapping when values exceed colormap bounds; Acer OpenXR rotation pivot fix for 3D displays; YAML handling fix to quote CCD codes to prevent integer parsing. - Observability and user guidance: Boltz GUI now monitors stderr and reports prediction progress, added sequence runtime reporting, logging of Boltz confidence scores; updated Boltz help pages and added a Boltz affinity prediction video link; UI feedback improvements such as a resize notification during movie crossfades and wider Boltz GUI prediction name field. Major bugs fixed: - AlphaFold Error Plot robustness: no error when input structure resides in an unlistable directory. - 2D TIFF stack opening: fixed errors when loading stacks of 2D TIFF images. - Surface color mapping: fixed color mapping for values beyond colormap bounds. - OpenXR Acer 3D display: fixed front-center rotation pivot issue. - Boltz edge cases: added error handling for CCD ligands Boltz does not know about (suggest using SMILES); corrected Boltz error plot model selection to show model 0 PAE; fixed YAML/CCD code parsing. Overall impact and accomplishments: - Substantial increase in platform coverage and model reliability with Boltz 2, enabling faster, more predictable ligand affinity predictions across major OSes. Hardware integration improvements provide smoother, more intuitive 3D visualization on Acer SpatialLabs, Sony, and Acer displays, enhancing collaboration and data interpretation. Code organization and observability gains reduce debugging time and improve user trust in the predictive pipeline. Technologies/skills demonstrated: - OpenXR integration and 3D display support; mouse/keyboard input handling; label rendering on hover. - Boltz 2 migration, cross-platform runtimes, and advanced UX for affinity predictions. - Code refactoring and modularization (mouse hover logic), error handling, YAML handling for CCD codes. - Telemetry, logging, and UI/UX improvements (GPU/CPU runtimes, help materials, and user feedback messages).
Monthly summary for 2025-07: Key features delivered: - Boltz 2 migration completed across Mac/Linux runtimes with affinity prediction; updated UI entries and improved error messaging for Boltz predictions. Includes new runtimes (Mac 16GB/32GB, Linux 64-bit) and per-ligand entries in the affinity menu. - OpenXR 3D display enhancements expanded to Acer SpatialLabs with reliable "xr on" activation; added mouse tracking and input support for Sony and Acer 3D displays; implemented atom and residue labels on hover. - Improved maintainability and UX: refactored mouse hover logic to decouple hover detection from the hover module, improving code organization and reliability. - Stability and data handling improvements: fixes for opening 2D TIFF stacks; surface color mapping when values exceed colormap bounds; Acer OpenXR rotation pivot fix for 3D displays; YAML handling fix to quote CCD codes to prevent integer parsing. - Observability and user guidance: Boltz GUI now monitors stderr and reports prediction progress, added sequence runtime reporting, logging of Boltz confidence scores; updated Boltz help pages and added a Boltz affinity prediction video link; UI feedback improvements such as a resize notification during movie crossfades and wider Boltz GUI prediction name field. Major bugs fixed: - AlphaFold Error Plot robustness: no error when input structure resides in an unlistable directory. - 2D TIFF stack opening: fixed errors when loading stacks of 2D TIFF images. - Surface color mapping: fixed color mapping for values beyond colormap bounds. - OpenXR Acer 3D display: fixed front-center rotation pivot issue. - Boltz edge cases: added error handling for CCD ligands Boltz does not know about (suggest using SMILES); corrected Boltz error plot model selection to show model 0 PAE; fixed YAML/CCD code parsing. Overall impact and accomplishments: - Substantial increase in platform coverage and model reliability with Boltz 2, enabling faster, more predictable ligand affinity predictions across major OSes. Hardware integration improvements provide smoother, more intuitive 3D visualization on Acer SpatialLabs, Sony, and Acer displays, enhancing collaboration and data interpretation. Code organization and observability gains reduce debugging time and improve user trust in the predictive pipeline. Technologies/skills demonstrated: - OpenXR integration and 3D display support; mouse/keyboard input handling; label rendering on hover. - Boltz 2 migration, cross-platform runtimes, and advanced UX for affinity predictions. - Code refactoring and modularization (mouse hover logic), error handling, YAML handling for CCD codes. - Telemetry, logging, and UI/UX improvements (GPU/CPU runtimes, help materials, and user feedback messages).
June 2025: Focused on improving user experience, data robustness, and command ergonomics in ChimeraX. Key work centered on AlphaFold Colab UX, PAE/Boltz data handling, and command usability enhancements, delivering business value by streamlining workflows, reducing errors, and enabling finer control over morph operations.
June 2025: Focused on improving user experience, data robustness, and command ergonomics in ChimeraX. Key work centered on AlphaFold Colab UX, PAE/Boltz data handling, and command usability enhancements, delivering business value by streamlining workflows, reducing errors, and enabling finer control over morph operations.
Month: 2025-05 — RBVI/ChimeraX delivered focused Boltz-related improvements across features, docs, cross‑platform support, and reliability. Notable features include Boltz media and help page enhancements, improved Boltz documentation/UX (including bfloat16 predictions and name-based results directories), GPU-enabled Boltz predictions on Windows, and usability improvements such as a Stop button and a single Save Default Options control. The month also expanded installation options and CUDA support, and strengthened the UI/CLI workflow with robust error handling and clearer documentation. These changes reduce time-to-run, improve cross‑platform stability, and enhance developer and user visibility into Boltz performance and configuration.
Month: 2025-05 — RBVI/ChimeraX delivered focused Boltz-related improvements across features, docs, cross‑platform support, and reliability. Notable features include Boltz media and help page enhancements, improved Boltz documentation/UX (including bfloat16 predictions and name-based results directories), GPU-enabled Boltz predictions on Windows, and usability improvements such as a Stop button and a single Save Default Options control. The month also expanded installation options and CUDA support, and strengthened the UI/CLI workflow with robust error handling and clearer documentation. These changes reduce time-to-run, improve cross‑platform stability, and enhance developer and user visibility into Boltz performance and configuration.
April 2025 monthly summary for RBVI/ChimeraX and timholy/boltz. Focus this month was on delivering the Boltz tooling as a first-class option within ChimeraX, expanding backend support, and stabilizing cross-platform installation and UX to maximize business value for researchers relying on high-throughput structure prediction workflows. The team delivered a functional Boltz structure prediction tool, added GPU/CPU device selection, expanded CLI/GUI options, and integrated daily build tooling and comprehensive documentation. A broad set of stability and usability fixes improved reliability across macOS, Windows, and Linux, and clarified error handling for GPU detection and session/marker operations. This work reduces setup friction, accelerates scientific workflows, and broadens adoption of Boltz within the ChimeraX ecosystem.
April 2025 monthly summary for RBVI/ChimeraX and timholy/boltz. Focus this month was on delivering the Boltz tooling as a first-class option within ChimeraX, expanding backend support, and stabilizing cross-platform installation and UX to maximize business value for researchers relying on high-throughput structure prediction workflows. The team delivered a functional Boltz structure prediction tool, added GPU/CPU device selection, expanded CLI/GUI options, and integrated daily build tooling and comprehensive documentation. A broad set of stability and usability fixes improved reliability across macOS, Windows, and Linux, and clarified error handling for GPU detection and session/marker operations. This work reduces setup friction, accelerates scientific workflows, and broadens adoption of Boltz within the ChimeraX ecosystem.
In March 2025, RBVI/ChimeraX delivered VR/OpenXR enhancements, plotting robustness, and cross‑platform maintenance that together raise enterprise VR usability, data reliability, and deployment readiness. Key VR work includes a new OpenXR mode toggle and improved rendering for Sony Spatial Reality, corrected VR zoom handling, camera position preservation on VR exit, and enhanced error messaging for Sony OpenXR, complemented by an update to PyOpenXR (1.1.4501). External-facing updates refreshed presentations/social links to reflect current Sony/BlueSky pages and the x.com domain. Visualization and plotting improvements hardened data handling and visuals across common workflows, including clearer clip labels, default AlphaFold PAE colormap, safer handling of empty data, and robust Gaussian volume validation; session restore fixes and avoidance of empty mutation plots were also implemented. Maintenance tasks improved cross‑platform reliability with macOS symlink fixes, Colab notebook compatibility updates, and build system cleanup. The combined impact is shorter cycle times for VR-enabled analyses, fewer interactive plotting issues, and smoother, lower-risk deployments across environments.
In March 2025, RBVI/ChimeraX delivered VR/OpenXR enhancements, plotting robustness, and cross‑platform maintenance that together raise enterprise VR usability, data reliability, and deployment readiness. Key VR work includes a new OpenXR mode toggle and improved rendering for Sony Spatial Reality, corrected VR zoom handling, camera position preservation on VR exit, and enhanced error messaging for Sony OpenXR, complemented by an update to PyOpenXR (1.1.4501). External-facing updates refreshed presentations/social links to reflect current Sony/BlueSky pages and the x.com domain. Visualization and plotting improvements hardened data handling and visuals across common workflows, including clearer clip labels, default AlphaFold PAE colormap, safer handling of empty data, and robust Gaussian volume validation; session restore fixes and avoidance of empty mutation plots were also implemented. Maintenance tasks improved cross‑platform reliability with macOS symlink fixes, Colab notebook compatibility updates, and build system cleanup. The combined impact is shorter cycle times for VR-enabled analyses, fewer interactive plotting issues, and smoother, lower-risk deployments across environments.
February 2025 monthly summary for RBVI/ChimeraX focusing on expanding data source compatibility, improving structural representation, and hardening stability to enable smoother workflows for researchers and downstream tools. The team delivered new data format support, enhanced mutation scoring with multi-chain and alignment controls, improved 3D labeling, and documentation improvements, alongside robustness fixes for edge cases in session handling and folding search results.
February 2025 monthly summary for RBVI/ChimeraX focusing on expanding data source compatibility, improving structural representation, and hardening stability to enable smoother workflows for researchers and downstream tools. The team delivered new data format support, enhanced mutation scoring with multi-chain and alignment controls, improved 3D labeling, and documentation improvements, alongside robustness fixes for edge cases in session handling and folding search results.
January 2025 monthly summary for RBVI/ChimeraX. The team delivered security patches, core stability improvements, and user-facing enhancements that strengthen research workflows and visualization capabilities. Highlights include compatibility updates for Python 3.11, improved IO/rendering reliability, and new visualization controls and documentation updates that support researchers across platforms.
January 2025 monthly summary for RBVI/ChimeraX. The team delivered security patches, core stability improvements, and user-facing enhancements that strengthen research workflows and visualization capabilities. Highlights include compatibility updates for Python 3.11, improved IO/rendering reliability, and new visualization controls and documentation updates that support researchers across platforms.
December 2024 (RBVI/ChimeraX) focused on delivering user-centric feature improvements, robust error handling, and targeted documentation enhancements to accelerate research workflows and improve reliability. Key outcomes include improved NMR constraint parsing and visualization, expanded troubleshooting guidance, crash-education enhancements in bug reporting, and integrated AlphaFold 3 resources for easier access to cutting-edge tools. Platform-specific fixes and data-missing handling further increased stability across macOS and data workflows, reducing support load and enabling faster research iteration.
December 2024 (RBVI/ChimeraX) focused on delivering user-centric feature improvements, robust error handling, and targeted documentation enhancements to accelerate research workflows and improve reliability. Key outcomes include improved NMR constraint parsing and visualization, expanded troubleshooting guidance, crash-education enhancements in bug reporting, and integrated AlphaFold 3 resources for easier access to cutting-edge tools. Platform-specific fixes and data-missing handling further increased stability across macOS and data workflows, reducing support load and enabling faster research iteration.
In November 2024, RBVI/ChimeraX delivered a set of UX enhancements, data ingestion improvements, and robustness fixes that strengthen research workflows, improve data interpretation, and expand support for AlphaFold-related data formats. The team focused on user-facing command UX, enhanced mutation scoring/visualization, and reliability across session saving and PDB handling, delivering business value through more efficient analyses and broader data compatibility.
In November 2024, RBVI/ChimeraX delivered a set of UX enhancements, data ingestion improvements, and robustness fixes that strengthen research workflows, improve data interpretation, and expand support for AlphaFold-related data formats. The team focused on user-facing command UX, enhanced mutation scoring/visualization, and reliability across session saving and PDB handling, delivering business value through more efficient analyses and broader data compatibility.

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