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Philips Healthcare maxent computer program
Maxent Computer 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
https://www.bioz.com/product/program+maxent/maxent+software/pm25236961-90-6-16
Average 90 stars, based on 1 article reviews
maxent computer program - by Bioz Stars, 2026-09
90/100 stars

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Article Title: Predicting the potential distribution of main malaria vectors Anopheles stephensi, An. culicifacies s.l. and An. fluviatilis s.l. in Iran based on maximum entropy model.
Article Snippet: Malaria is considered as a major public health problem in southern areas of Iran.. The goal of this study was to predict best ecological niches of three main malaria vectors of Iran: Anopheles stephensi, Anopheles culicifacies s.l. and Anopheles fluviatilis s.l.. A databank was created which included all published data about Anopheles species of Iran from 1961 to 2015.

Software:

Article Title: Modeling potential distribution and above-ground biomass of Scots pine (Pinus sylvestris L.) forests in the Inner Anatolian Region, Türkiye.
Article Snippet: Scots pine (Pinus sylvestris L.) holds a substantial position as a tree species designated for biomass energy within European forests, covering a significant part of Türkiye’s forests.. We used the machine learning technique, namely, maximum entropy (MaxEnt), to estimate the suitable areas for Scots pine and to investigate its potential future distribution under various climate change scenarios in Inner Anatolian Region, Türkiye.. The distribution data of Scots pine was utilized, and a set of 20 variables was chosen from spectral, topographic, and bioclimatic datasets to train the MaxEnt model. A map depicting the potential distribution of Scots pine in the area was generated, and alterations in its spatial distribution under SSP2-4.5 and SSP5-8.5 climate change scenarios were predicted.

Article Title: Neotropical Leaf Litter Beetle Genus Motonerus (Coleoptera: Hydrophilidae): New Species, Distribution Data, and Description of Third Instar Larva.
Article Snippet: SYSTEMATICS, MORPHOLOGY AND PHYSIOLOGY Neotropical Leaf Litter Beetle Genus Motonerus (Coleoptera:

Article Title: Evaluating the vulnerability of Tetracentron sinense habitats to climate‐induced latitudinal shifts
Article Snippet: .. Optimal model parameters, indicated by the lowest AICc value, were selected for utilization within the MaxEnt software (Philips et al., ). ..

Article Title: Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis.
Article Snippet: Female Ae. aegypti and Ae. albopictus mosquitoes were stored in vials with an RNAlater® solution from (ThermoFisher) https://www.thermofisher.com/co) for subsequent analysis of the presence of Dengue Virus (DENV) using molecular techniques. .. Spatial information on the potential distribution of Aedes mosquitoes in the municipality of Piamonte were generated using MaxEnt software (Philips et al., 2024), which allows modelling the geographic distribution of the species from environmental and georeferenced data from field sampling. ..

Article Title: Palawan Peacock Pheasant (Polyplectron Napoleonis) Species Distribution Modeling: A Review of the Impact of Typhoon Rai/Odette on the Diversity and Distribution of an Endemic Bird Species
Article Snippet: This study quantified the habitat requirements and, consequently, described the remaining suitable habitats through species distribution modeling of Polyplectron napoleonis within Cleopatra’s Needle Forest Reserve and Puerto Princesa Subterranean River National Park after the onslaught of Typhoon Odette in the Palawan region.. This was accomplished using MaxEnt software, a statistical machine-learning algorithm that creates niche models with presence-only (PO) data and surrounding environmental variables (Dudik et al., 2007; Merow et al., 2013).. Previous studies have identified precipitation, elevation, and land cover as the top environmental variables influencing tandikan habitat suitability, as revealed by their percent contributions.

Article Title: Quantifying the distribution and site fidelity of a rare, non-commercial elasmobranch using local ecological knowledge
Article Snippet: Fishery catch records offer limited data to assess the status of rare, non-commercial species, including some sharks.. Despite marine megafauna creating an important source of revenue though tourism, basic spatial information required to create conservation strategies is not available for many of these species.. A cost-effective approach to assess the distribution of rare, non-commercial species is required to manage resources and inform conservation strategies in data-deficient areas.

Article Title: Burn severity analysis in Mediterranean forests using maximum entropy model trained with EO-1 Hyperion and LiDAR data
Article Snippet: All ecosystems and in particular ecosystems in Mediterranean climates are affected by fires.. Knowledge of the drivers that most influence burn severity patterns as well an accurate map of post-fire effects are key tools for forest managers in order to plan an adequate post-fire response.. Remote sensing data are becoming an indispensable instrument to reach both objectives.

Generated:

Article Title: Neotropical Leaf Litter Beetle Genus Motonerus (Coleoptera: Hydrophilidae): New Species, Distribution Data, and Description of Third Instar Larva.
Article Snippet: SYSTEMATICS, MORPHOLOGY AND PHYSIOLOGY Neotropical Leaf Litter Beetle Genus Motonerus (Coleoptera:

Article Title: Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis.
Article Snippet: Female Ae. aegypti and Ae. albopictus mosquitoes were stored in vials with an RNAlater® solution from (ThermoFisher) https://www.thermofisher.com/co) for subsequent analysis of the presence of Dengue Virus (DENV) using molecular techniques. .. Spatial information on the potential distribution of Aedes mosquitoes in the municipality of Piamonte were generated using MaxEnt software (Philips et al., 2024), which allows modelling the geographic distribution of the species from environmental and georeferenced data from field sampling. ..

Sampling:

Article Title: Dengue risk-mapping in an Amazonian locality in Colombia based on regression and multi-criteria analysis.
Article Snippet: Female Ae. aegypti and Ae. albopictus mosquitoes were stored in vials with an RNAlater® solution from (ThermoFisher) https://www.thermofisher.com/co) for subsequent analysis of the presence of Dengue Virus (DENV) using molecular techniques. .. Spatial information on the potential distribution of Aedes mosquitoes in the municipality of Piamonte were generated using MaxEnt software (Philips et al., 2024), which allows modelling the geographic distribution of the species from environmental and georeferenced data from field sampling. ..



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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
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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 Computer 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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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