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Philips Healthcare maxent program
Maxent Program, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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maxent program - by Bioz Stars, 2026-11
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Article Title: An ecological niche model that considers local relationships among variables: The Environmental String Model
Article Snippet: According to the types of data on which such models can be applied, three families can be distinguished: (1) models that work on presence-only data such as the ecological niche factor analysis (ENFA; Hirzel et al., 2002), MaxEnt (Philips et al., 2006), and the nonparametric probabilistic ecological niche (NPPEN) model (Beaugrand et al., 2011); (2) models that work on presence/absence data such as generalized linear models (GLMs) (McCullagh & Nelder, 1983), generalized additive models (GAMs) (Hastie & Tibshirani, 1990), and random forests (Zhang et al., 2019); and (3) models working on abundance data such as generalized regression neural network (GRNN) (Specht, 1991), GLMs, and GAMs.

Article Title: Common dolphin's shipping noise risk assessment on the Portuguese coast.
Article Snippet: This methodology is fully detailed in Fernandez et al. (Fernandez et al., 2021) in which the combination of the target species' observation records and the target area's environmental characteristics was used to perform an Ecological Niche Model (ENM) through a maximum entropy algorithm called MAXENT (Philips et al., 2018).

Article Title: Evolutionary origins, macroevolutionary dynamics, and climatic niche space of the succulent plant syndrome in the Caryophyllales.
Article Snippet: We estimated ENMs for every species on these datasets by using MaxEnt (Philips et al., 2006), with the environmental variables described in the previous section but with a downscaled resolution of 2.5 arc minutes (~5 km at the equator).

Article Title: Integrating habitat suitability modeling with gene flow improves delineation of landscape connections among African savanna elephants
Article Snippet: We parameterized a commonly used presence-only habitat suitability model, MaxEnt (Philips et al. 2006, 2017).

Article Title: Connecting Habitats: Modelling Landscape Connectivity for Large Mammals in Omo-Shasha-Oluwa Forest Reserves, South-West Nigeria
Article Snippet: We created a species distribution model using the presence-only occurrence data for each of the seven large mammal species detected above using the machine learning algorithm implemented in Program MaxEnt (Philips et al., 2006).

Software:

Article Title: Spatial and Temporal Patterns of Campylobacter Infection and Projected Habitat Suitability of Dominant Campylobacter Species in Eastern Ethiopia
Article Snippet: .. MaxEnt (Version 3.4.4) software (Philips et al., ) was used to model the potential geographic distribution of the genus Campylobacter as well as two dominant species identified by PCR results, C. jejuni and C. infans , over the study area (Deblais et al., ). ..

Polymerase Chain Reaction:

Article Title: Spatial and Temporal Patterns of Campylobacter Infection and Projected Habitat Suitability of Dominant Campylobacter Species in Eastern Ethiopia
Article Snippet: .. MaxEnt (Version 3.4.4) software (Philips et al., ) was used to model the potential geographic distribution of the genus Campylobacter as well as two dominant species identified by PCR results, C. jejuni and C. infans , over the study area (Deblais et al., ). ..



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Program Maxent, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
Maxent Program, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the <t>MaxEnt</t> program were edited with <t>the</t> <t>ArcGIS</t> software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa
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Image Search Results


Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the MaxEnt program were edited with the ArcGIS software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa

Journal: Brazilian Journal of Microbiology

Article Title: Geographical distribution and ecological niche modeling of the etiological agents of human sporotrichosis in Venezuela

doi: 10.1007/s42770-020-00306-0

Figure Lengend Snippet: Geographical distributions predicted for Sporothrix spp. in Venezuela. The geographical distribution of the Sporothrix species is based on the optimal environmental conditions predicted by the ENM. The images generated as an output by the MaxEnt program were edited with the ArcGIS software suite, version 10.0. Panel a, geographic distribution predicted for S. schenckii. Panel b, geographical distribution predicted for S. globosa

Article Snippet: The images in raster format generated as an output by the MaxEnt program were edited with the help of the ArcGIS software suite, version 10.0 (Environmental Systems Research Institute (ESRI), Redlands, CA, USA) to generate the distribution map for each Sporothrix species (Fig. , panels a and b).

Techniques: Generated, Software