open-source toolboxes and plugins Search Results


source plugin  (Oxford Instruments)
99
Oxford Instruments source plugin
Source Plugin, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/source plugin/product/Oxford Instruments
Average 99 stars, based on 1 article reviews
source plugin - by Bioz Stars, 2026-06
99/100 stars
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open-source plugin difffit  (Nanovis Inc)
90
Nanovis Inc open-source plugin difffit
Open Source Plugin Difffit, supplied by Nanovis Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/open-source plugin difffit/product/Nanovis Inc
Average 90 stars, based on 1 article reviews
open-source plugin difffit - by Bioz Stars, 2026-06
90/100 stars
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imagej plugins  (KNIME GmbH)
90
KNIME GmbH imagej plugins
NR-SAT single-cell segmentation and tracking scheme. (Phase 1) The input nuclear channel is illumination-corrected using background subtraction, followed by local contrast enhancement. The resulting images then undergo thresholding (Mean method) and are dilated and then labeled. An object filter is applied to remove threshold artifacts prior to converting the images into binary images and filling holes. Finally, the data is passed to the Wählby Cell Clump Splitter, which separates nuclei that are in proximity to one another. (Phase 2) These data are then passed to the nuclei tracking nodes where the <t>ImageJ</t> plugin TrackMate is implemented to track each cell, accounting for splitting and merging events. (Phase 3) After the nuclei are tracked, the nuclear mask is duplicated and dilated (number of dilations is user-defined and applied to all images in the same manner, 10× in this example) to generate two masks, where the newly dilated mask is larger than the original source mask. These two masks (the newly larger dilated mask and the smaller original mask) are then segmented via the Voronoi segmentation node, generating cytoplasmic rings that are approximately a fixed pixel-width. (Phase 4) Finally these cytoplasmic rings, along with the nuclear masks, are applied to the measurement channel(s) and written to a CSV output file.
Imagej Plugins, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/imagej plugins/product/KNIME GmbH
Average 90 stars, based on 1 article reviews
imagej plugins - by Bioz Stars, 2026-06
90/100 stars
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plugins  (KNIME GmbH)
90
KNIME GmbH plugins
NR-SAT single-cell segmentation and tracking scheme. (Phase 1) The input nuclear channel is illumination-corrected using background subtraction, followed by local contrast enhancement. The resulting images then undergo thresholding (Mean method) and are dilated and then labeled. An object filter is applied to remove threshold artifacts prior to converting the images into binary images and filling holes. Finally, the data is passed to the Wählby Cell Clump Splitter, which separates nuclei that are in proximity to one another. (Phase 2) These data are then passed to the nuclei tracking nodes where the <t>ImageJ</t> plugin TrackMate is implemented to track each cell, accounting for splitting and merging events. (Phase 3) After the nuclei are tracked, the nuclear mask is duplicated and dilated (number of dilations is user-defined and applied to all images in the same manner, 10× in this example) to generate two masks, where the newly dilated mask is larger than the original source mask. These two masks (the newly larger dilated mask and the smaller original mask) are then segmented via the Voronoi segmentation node, generating cytoplasmic rings that are approximately a fixed pixel-width. (Phase 4) Finally these cytoplasmic rings, along with the nuclear masks, are applied to the measurement channel(s) and written to a CSV output file.
Plugins, supplied by KNIME GmbH, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/plugins/product/KNIME GmbH
Average 90 stars, based on 1 article reviews
plugins - by Bioz Stars, 2026-06
90/100 stars
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open source matlab toolbox eeglab  (MathWorks Inc)
96
MathWorks Inc open source matlab toolbox eeglab
NR-SAT single-cell segmentation and tracking scheme. (Phase 1) The input nuclear channel is illumination-corrected using background subtraction, followed by local contrast enhancement. The resulting images then undergo thresholding (Mean method) and are dilated and then labeled. An object filter is applied to remove threshold artifacts prior to converting the images into binary images and filling holes. Finally, the data is passed to the Wählby Cell Clump Splitter, which separates nuclei that are in proximity to one another. (Phase 2) These data are then passed to the nuclei tracking nodes where the <t>ImageJ</t> plugin TrackMate is implemented to track each cell, accounting for splitting and merging events. (Phase 3) After the nuclei are tracked, the nuclear mask is duplicated and dilated (number of dilations is user-defined and applied to all images in the same manner, 10× in this example) to generate two masks, where the newly dilated mask is larger than the original source mask. These two masks (the newly larger dilated mask and the smaller original mask) are then segmented via the Voronoi segmentation node, generating cytoplasmic rings that are approximately a fixed pixel-width. (Phase 4) Finally these cytoplasmic rings, along with the nuclear masks, are applied to the measurement channel(s) and written to a CSV output file.
Open Source Matlab Toolbox Eeglab, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/open source matlab toolbox eeglab/product/MathWorks Inc
Average 96 stars, based on 1 article reviews
open source matlab toolbox eeglab - by Bioz Stars, 2026-06
96/100 stars
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hanalyzer  (SourceForge net)
90
SourceForge net hanalyzer
A system diagram describing the modules of the <t>Hanalyzer.</t> Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.
Hanalyzer, supplied by SourceForge net, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/hanalyzer/product/SourceForge net
Average 90 stars, based on 1 article reviews
hanalyzer - by Bioz Stars, 2026-06
90/100 stars
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chemaxon plugin calculators  (ChemAxon LLC)
90
ChemAxon LLC chemaxon plugin calculators
A system diagram describing the modules of the <t>Hanalyzer.</t> Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.
Chemaxon Plugin Calculators, supplied by ChemAxon LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/chemaxon plugin calculators/product/ChemAxon LLC
Average 90 stars, based on 1 article reviews
chemaxon plugin calculators - by Bioz Stars, 2026-06
90/100 stars
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chemaxon’s conformer plugin  (ChemAxon LLC)
90
ChemAxon LLC chemaxon’s conformer plugin
A system diagram describing the modules of the <t>Hanalyzer.</t> Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.
Chemaxon’s Conformer Plugin, supplied by ChemAxon LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/chemaxon’s conformer plugin/product/ChemAxon LLC
Average 90 stars, based on 1 article reviews
chemaxon’s conformer plugin - by Bioz Stars, 2026-06
90/100 stars
  Buy from Supplier
marvin calculator plugins  (ChemAxon LLC)
90
ChemAxon LLC marvin calculator plugins
A system diagram describing the modules of the <t>Hanalyzer.</t> Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.
Marvin Calculator Plugins, supplied by ChemAxon LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/marvin calculator plugins/product/ChemAxon LLC
Average 90 stars, based on 1 article reviews
marvin calculator plugins - by Bioz Stars, 2026-06
90/100 stars
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open source plugin to pymol  (SourceForge net)
90
SourceForge net open source plugin to pymol
The ProMOL GUI was created using Tkinter <t>(</t> <t>http://wiki.python.org/moin/TkInter</t> ). Each tab gives the user access to collections of features in ProMOL. The EZ-Viz and View Options tabs allow the user to manipulate the appearance of loaded structures and the <t>PyMOL</t> interface, respectively. Motif Finder is an interface for querying structures against the motif template library. Motif Maker allows users to create their own motif templates for structure analysis.
Open Source Plugin To Pymol, supplied by SourceForge net, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/open source plugin to pymol/product/SourceForge net
Average 90 stars, based on 1 article reviews
open source plugin to pymol - by Bioz Stars, 2026-06
90/100 stars
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array analyze  (Active Motif)
90
Active Motif array analyze
The ProMOL GUI was created using Tkinter <t>(</t> <t>http://wiki.python.org/moin/TkInter</t> ). Each tab gives the user access to collections of features in ProMOL. The EZ-Viz and View Options tabs allow the user to manipulate the appearance of loaded structures and the <t>PyMOL</t> interface, respectively. Motif Finder is an interface for querying structures against the motif template library. Motif Maker allows users to create their own motif templates for structure analysis.
Array Analyze, supplied by Active Motif, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/array analyze/product/Active Motif
Average 90 stars, based on 1 article reviews
array analyze - by Bioz Stars, 2026-06
90/100 stars
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bim based carbo life calculator  (Autodesk Inc)
86
Autodesk Inc bim based carbo life calculator
The ProMOL GUI was created using Tkinter <t>(</t> <t>http://wiki.python.org/moin/TkInter</t> ). Each tab gives the user access to collections of features in ProMOL. The EZ-Viz and View Options tabs allow the user to manipulate the appearance of loaded structures and the <t>PyMOL</t> interface, respectively. Motif Finder is an interface for querying structures against the motif template library. Motif Maker allows users to create their own motif templates for structure analysis.
Bim Based Carbo Life Calculator, supplied by Autodesk Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/bim based carbo life calculator/product/Autodesk Inc
Average 86 stars, based on 1 article reviews
bim based carbo life calculator - by Bioz Stars, 2026-06
86/100 stars
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Image Search Results


NR-SAT single-cell segmentation and tracking scheme. (Phase 1) The input nuclear channel is illumination-corrected using background subtraction, followed by local contrast enhancement. The resulting images then undergo thresholding (Mean method) and are dilated and then labeled. An object filter is applied to remove threshold artifacts prior to converting the images into binary images and filling holes. Finally, the data is passed to the Wählby Cell Clump Splitter, which separates nuclei that are in proximity to one another. (Phase 2) These data are then passed to the nuclei tracking nodes where the ImageJ plugin TrackMate is implemented to track each cell, accounting for splitting and merging events. (Phase 3) After the nuclei are tracked, the nuclear mask is duplicated and dilated (number of dilations is user-defined and applied to all images in the same manner, 10× in this example) to generate two masks, where the newly dilated mask is larger than the original source mask. These two masks (the newly larger dilated mask and the smaller original mask) are then segmented via the Voronoi segmentation node, generating cytoplasmic rings that are approximately a fixed pixel-width. (Phase 4) Finally these cytoplasmic rings, along with the nuclear masks, are applied to the measurement channel(s) and written to a CSV output file.

Journal: Viruses

Article Title: HIV RGB: Automated Single-Cell Analysis of HIV-1 Rev-Dependent RNA Nuclear Export and Translation Using Image Processing in KNIME

doi: 10.3390/v14050903

Figure Lengend Snippet: NR-SAT single-cell segmentation and tracking scheme. (Phase 1) The input nuclear channel is illumination-corrected using background subtraction, followed by local contrast enhancement. The resulting images then undergo thresholding (Mean method) and are dilated and then labeled. An object filter is applied to remove threshold artifacts prior to converting the images into binary images and filling holes. Finally, the data is passed to the Wählby Cell Clump Splitter, which separates nuclei that are in proximity to one another. (Phase 2) These data are then passed to the nuclei tracking nodes where the ImageJ plugin TrackMate is implemented to track each cell, accounting for splitting and merging events. (Phase 3) After the nuclei are tracked, the nuclear mask is duplicated and dilated (number of dilations is user-defined and applied to all images in the same manner, 10× in this example) to generate two masks, where the newly dilated mask is larger than the original source mask. These two masks (the newly larger dilated mask and the smaller original mask) are then segmented via the Voronoi segmentation node, generating cytoplasmic rings that are approximately a fixed pixel-width. (Phase 4) Finally these cytoplasmic rings, along with the nuclear masks, are applied to the measurement channel(s) and written to a CSV output file.

Article Snippet: NR-SAT represents an intuitive open-source method for single-cell tracking, reliable nucleus vs. cytoplasm cell segmentation, and fluorescence intensity measurements using ImageJ plugins [ , ] integrated into the open source KNIME analytics platform [ ].

Techniques: Labeling

A system diagram describing the modules of the Hanalyzer. Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.

Journal: PLoS Computational Biology

Article Title: Biomedical Discovery Acceleration, with Applications to Craniofacial Development

doi: 10.1371/journal.pcbi.1000215

Figure Lengend Snippet: A system diagram describing the modules of the Hanalyzer. Reading methods (green) take external sources of knowledge (blue) and extract information from them, either by parsing structured data or biomedical language processing to extract information from unstructured data. Reading modules are responsible for tracking the provenance of all knowledge. Reasoning methods (yellow) enrich the knowledge that results from reading by, for example, noting two genes that are annotated to the same ontology term or database entry. All knowledge sources, read or reasoned, are assigned a reliability score, and all are combined using that score into a knowledge network (orange) that represents the integration of all sorts of relationship between a pair of genes and a combined reliability score. A data network (also orange) is created from experimental results to be analyzed. The reporting modules (pink) integrate the data and knowledge networks, producing visualizations that can be queried with the associated drill-down tool.

Article Snippet: The Hanalyzer, including the experts and the Cytoscape plugin for visualization is available as open source software via SourceForge at hanalyzer.sourceforge.net.

Techniques:

The ProMOL GUI was created using Tkinter ( http://wiki.python.org/moin/TkInter ). Each tab gives the user access to collections of features in ProMOL. The EZ-Viz and View Options tabs allow the user to manipulate the appearance of loaded structures and the PyMOL interface, respectively. Motif Finder is an interface for querying structures against the motif template library. Motif Maker allows users to create their own motif templates for structure analysis.

Journal: BMC Bioinformatics

Article Title: Estimation of protein function using template-based alignment of enzyme active sites

doi: 10.1186/1471-2105-15-87

Figure Lengend Snippet: The ProMOL GUI was created using Tkinter ( http://wiki.python.org/moin/TkInter ). Each tab gives the user access to collections of features in ProMOL. The EZ-Viz and View Options tabs allow the user to manipulate the appearance of loaded structures and the PyMOL interface, respectively. Motif Finder is an interface for querying structures against the motif template library. Motif Maker allows users to create their own motif templates for structure analysis.

Article Snippet: Its design as an open source ( http://sourceforge.net/projects/sbevsl/files/ProMOL/ ) plugin to PyMOL is conducive to customization and further development by independent users.

Techniques: