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 | align="center" | bio
 | align="center" | 3.0.4
-| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: BayesAss: Bayesian Inference of Recent Migration Using Multilocus Genotypes Homepage: http://www.rannala.org/?page_id=245 Keyword:bio<br /><br /><br /></div>
+| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: BayesAss: Bayesian Inference of Recent Migration Using Multilocus Genotypes Homepage: http://www.rannala.org/?page_id=245 URL: http://www.rannala.org/?page_id=245 Keyword:bio<br /><br /><br /></div>
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 | align="center" | [http://www.rannala.org/inference-of-recent-migration bayesass3-snps]
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 | align="center" | math
 | align="center" | 4.0.3, 5.1.0
-| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes. Homepage: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview Keyword:math<br /><br /><br /></div>
+| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: METIS is a set of serial programs for partitioning graphs, partitioning finite element meshes, and producing fill reducing orderings for sparse matrices. The algorithms implemented in METIS are based on the multilevel recursive-bisection, multilevel k-way, and multi-constraint partitioning schemes. Homepage: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview URL: http://glaros.dtc.umn.edu/gkhome/metis/metis/overview Keyword:math<br /><br /><br /></div>
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 | align="center" | [http://glaros.dtc.umn.edu/gkhome/metis/metis/overview metis-64idx]
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 | align="center" | [https://repast.github.io/ repasthpc]
 | align="center" | bio
-| align="center" | 2.2.0, 2.3.0
+| align="center" | 2.0, 2.2.0, 2.3.0
 | <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: The Repast Suite is a family of advanced, free, and open source agent-based modeling and simulation platforms that have collectively been under continuous development for over 15 years: Repast for High Performance Computing 2.2.0, released on 30 September 2016, is a lean and expert-focused C++-based modeling system that is designed for use on large computing clusters and supercomputers. Homepage: https://repast.github.io/ URL: https://repast.github.io/ Keyword:bio<br /><br /><br /></div>
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 | align="center" | 6.0.1.5, 8.6.1.6
-| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: python/3.10, python/3.11<br /><br /><br /></div>
+| <div class="mw-collapsible mw-collapsed" style="white-space: pre-line;"><br />Description: NVIDIA TensorRT is a platform for high-performance deep learning inference Homepage: https://developer.nvidia.com/tensorrt URL: https://developer.nvidia.com/tensorrt Compatible modules: python/3.8, python/3.9, python/3.10, python/3.11<br /><br /><br /></div>
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 | align="center" | [https://github.com/tesseract-ocr/tesseract tesseract]