U.S. flag

An official website of the United States government

Gerris buenoi Genome Assembly 1.0

    The Baylor College of Medicine recently sequenced and annotated the Gerris buenoi genome as part of the i5k pilot project. This dataset presents the Gerris buenoi genome v1.0. This assembly version is the pre-release version, prior to filtering and quality control by the National Center for Biotechnology Information's GenBank resource. The corresponding genome assembly in [GCA_001010745.1](https://www.ncbi.nlm.nih.gov/assembly/GCA_001010745.1/)

    Gerris buenoi genome annotations v0.5.3

      The Gerris buenoi genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. This dataset presents the Gerris buenoi gene set BCM_v_0.5.3, which was generated computationally. RNA-Seq data was used with additional protein homology data for a MAKER automated annotation of the Gerris buenoi genome assembly 1.0. NOTE: This gene set is an unstable pre-release (v0.5.3), and was provided to facilitate manual curation and analyses before the official gene set is released. Gene identifiers from this gene set will likely not be maintained.

      Gerris buenoi Official Gene set v1.0

        The Gerris buenoi genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Gerris buenoi research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The OGS is an integration of automatic gene predictions from Maker (performed by Dan Hughes at Baylor College of Medicine) with manual annotations by the research community (done via the Apollo manual annotation software).

        Hyalella azteca Genome Annotations v0.5.3

          The Baylor College of Medicine recently sequenced and annotated the Hyalella azteca genome as part of the i5k pilot project. This dataset presents the Hyalella azteca gene set BCM_v_0.5.3, which was generated computationally. RNA-Seq data was used with additional protein homology data for a MAKER automated annotation of the Hyalella azteca genome assembly 1.0. Further annotation method details will be available in a forthcoming publication.

          NOTE: This gene set is an unstable pre-release (v0.5.3), and was provided to facilitate manual curation and analyses before the official gene set is released. Gene identifiers from this gene set will likely not be maintained.

          Hyalella azteca Genome Assembly 1.0

            The Baylor College of Medicine recently sequenced and annotated the Hyalella azteca genome as part of the i5k pilot project. The Hyalella azteca research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. This dataset presents the Hyalella azteca genome v1.0. This assembly version is the pre-release version, prior to filtering and quality control by the National Center for Biotechnology Information's GenBank resource. The corresponding genome assembly in NCBI is [GCA_000764305.1](https://www.ncbi.nlm.nih.gov/assembly/GCA_000764305.1).

            Insect Images: The Source for Entomology Photos

              A joint project of The University of Georgia - Warnell School of Forestry and Natural Resources, College of Agricultural and Environmental Sciences - Department of Entomology, Center for Invasive Species and Ecosystem Health, Georgia Museum of Natural History, The Entomology Society of America and USDA Identification Technology Program, [Insect Images](https://www.insectimages.org/) image categories include: Insect Orders: Hymenoptera; Coleoptera; Hemiptera; Lepidoptera; Blattodea; Odonata; Dermaptera; Diptera; Orthoptera; Neuroptera; Phthiraptera; Mantodea; Thysanura; Isoptera; Thysanoptera; Phasmatoptera; and Related Organisms.

              Weed Images: The Source for Images of Weeds and Weed Management in Agriculture

                A joint project of The University of Georgia - Warnell School of Forestry and Natural Resources, College of Agricultural and Environmental Sciences - Department of Entomology, Center for Invasive Species and Ecosystem Health, Weed Science Society of America and the USDA/APHIS Identification Technology Program, [Weed Images](https://www.weedimages.org/) image categories include: Habit: Aquatics, Herbs/Forbs, Grasses, Shrubs, Trees, Vines; Herbicides: Mechanism of Action, HRAC or WSSA Group; Most Troublesome and Most Common Weed Lists.

                Hyalella azteca Official Gene Set v1.0

                  The Hyalella azteca genome was recently sequenced and annotated as part of the i5k pilot project by the Baylor College of Medicine. The Hyalella azteca research community has manually reviewed and curated the computational gene predictions and generated an official gene set, OGSv1.0. The OGS is an integration of automatic gene predictions from Maker with manual annotations by the research community (via the Apollo manual annotation software).

                  Forestry Images: The Source for Forest Health and Silviculture Images

                    A joint project between University of Georgia - Bugwood Network and the U.S. Department of Agriculture, [Forestry Images](https://www.forestryimages.org/) image categories include: Forest Pests; Trees, Plants, and Stand Types; Silvicultural Practices; Urban Forestry; Wildlife; People, Places and Scenes.

                    National Integrated Pest Management (IPM) Database - IPMdata

                      Integrated Pest Management (IPM) is a science-based, decision-making process that identifies and reduces risks from pests and pest management related strategies. IPM coordinates the use of pest biology, environmental information, and available technology to prevent unacceptable levels of pest damage by the most economical means, while minimizing risk to people, property, resources, and the environment. IPM provides an effective strategy for managing pests in all arenas from developed agricultural, residential, and public lands to natural and wilderness areas. IPM provides an effective, all encompassing, low-risk approach to protect resources and people from pests.