Tools   Select Another Resource Report Type

http://www.vetmed.lsu.edu/Summer_Scholars_Program.htm

The aim of the Summer Scholars Program is to provide veterinary medical students the opportunity to explore the world of biomedical research, develop and complete a biomedical research project during the summer. The intent is to engage students in a creative, problem-solving research activity and to provide a learning experience that will lead to the discovery of new knowledge in an area of their choosing and identify potential pathways to a career in biomedical research. Research plans will be developed by students with faculty mentor input, on any topic of interest to the student and likely to lead to the discovery of new information. Example topics are: immunology and infectious diseases, cancer biology, molecular epidemiology, experimental studies focused on nutrition and obesity, pharmacology, environmental toxicology, mechanisms of pathogenesis, zoonoses, biomechanics, cardiovascular pathophysiology, and others. The mentor and other advisors will provide guidance to students and an assessment of progress. Students will provide at completion of the study, an oral presentation of their results to their colleagues and all mentors and a presentation of results via posters at the annual Merial NIH National Veterinary Scholars Symposium, to be held in 2010 at the University of Georgia, and at the LSU Phi Zeta Research Emphasis Day. It is noteworthy that one Summer Scholar won an award at the 2008 LSU Phi Zeta Research Emphasis Day. LSU Students will receive elective credit in the curriculum (VMED 5010 or VMED 5463) for successful completion of the program. Students will be strongly encouraged to work with their mentors to publish their findings in peer-reviewed journals separately or as a smaller piece of work with their mentors. Sponsors: The program is funded by a Merial Foundation grant and an NIH T35 training grant.

Proper citation: Merial/NIH Veterinary Scholars Program (RRID:SCR_008301) Copy   

•   Source: SciCrunch Registry

http://www.vetmed.wisc.edu/ms-phd/

The Comparative Biomedical Sciences Graduate Degree program provides exceptional graduate research training in core areas of animal and human health including genomics, immunology, molecular and cellular biology, physiology, infectious disease, neuroscience, pharmacology and toxicology, and oncology. Seventy-five faculty members in a diverse number of UW departments including Bacteriology, Biochemistry, Medical Microbiology and Immunology, Medicine, Oncology, Pathology, Radiology in addition to the 4 departments of the School of Veterinary Medicine are trainers in the program. These internationally recognized professors, as well as the integrative nature of our program, provide outstanding and unique research opportunities for our students. Because the University of Wisconsin is consistently ranked as one of the best 10 graduate institutions in the nation, the strength of our program is not only due to the superb research and teaching of our faculty but also due to the University as a whole. Approximately 55 students, most of whom are Ph.D. candidates, are currently enrolled in the program. Research strategies and academic curricula are tailored to the specific needs of each individual student. Graduates from our program are highly successful in the biotechnology industry and at top-ranked research institutions in the U.S. and abroad. The Comparative Biomedical Sciences Graduate Program offers a diverse number of research opportunities in multiple fields of study. A brief description of some of the major areas of research being performed by faculty affiliated with the Comparative Biomedical Sciences Graduate Program is provided below. Use the pull down menu above or click on the heading to find faculty members doing research in these areas. Sponsors: CBMS is supported by the University of Wisconsin

Proper citation: Comparative Biomedical Sciences Graduate Program (RRID:SCR_008304) Copy   

•   Source: SciCrunch Registry

http://code.google.com/

Developer tools, APIs and resources. Search developers.google.com and code.google.com.

Proper citation: Google Code (RRID:SCR_005786) Copy   

•   Source: SciCrunch Registry

http://collaborations.gis.a-star.edu.sg/~cmb6/TherMos/

Software used for estimating protein-DNA binding energies from in vivo binding profiles. It is a de novo motif discovery algorithm that exploits the information in transcription factor ChIP-seq or ChIP-exo datasets based on a more natural thermodynamic formalism., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: TherMos (RRID:SCR_002790) Copy   

•   Source: SciCrunch Registry

http://www.ig.utexas.edu/sdc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Database of processed seismic reflection / refraction data providing access to metadata, SEG-Y files, navigation files, seismic profile images, processing histories and more. The main features of the web site include a geographic search engine using Google Plugins, a metadata search engine, and metadata pages for the various seismic programs. Metadata are uploaded into mySQL, a public-domain SQL server, and then PHP scripts query the metadata and directories, creating web pages, displaying images, and providing ftp links.

Proper citation: Academic Seismic Portal at UTIG (RRID:SCR_000403) Copy   

•   Source: SciCrunch Registry

https://www.pgscatalog.org/

Open database of polygenic scores and relevant metadata required for accurate application and evaluation. Used for reproducibility and systematic evaluation.

Proper citation: Polygenic Score Catalog (RRID:SCR_023558) Copy   

•   Source: SciCrunch Registry

https://cdip.ucsd.edu/

Network for monitoring waves and beaches and prediction of waves and shoreline change along coastlines of United States. Since 1975 program has produced database of publicly accessible environmental data for use by coastal engineers and planners, scientists, mariners, and marine enthusiasts. Forefront of coastal monitoring, developing numerous innovations in instrumentation, system control and management, computer hardware and software, field equipment, and installation techniques. Operated by Ocean Engineering Research Group, part of Integrative Oceanography Division at Scripps Institution of Oceanography. CDIP measures, analyzes, archives and disseminates coastal environment data for use by coastal engineers, planners and managers, as well as scientists and mariners.

Proper citation: Coastal Data Information Program (RRID:SCR_024649) Copy   

•   Source: SciCrunch Registry

https://open.oncobox.com/

Structured curated collection of protein based and of metabolic human molecular pathways. Human molecular pathways database with tools for activity calculating and visualization.All pathways are functionally classified according to GO terms enrichment patterns. All pathway participants, their interactions and reactions are uniformly processed and annotated, and are ready for numeric analysis of experimental expression data.For every comparison graph is generated summarizing top up and down regulated pathways.

Proper citation: OncoboxPD (RRID:SCR_023723) Copy   

•   Source: SciCrunch Registry

https://kanphos.neuroinf.jp/

Database system that provides phosphorylated sites and information about which substrates are phosphorylated by specific kinase and which extracellular stimuli activate or inhibit protein phosphorylation via intracellular signaling cascades.

Proper citation: Kinase Associated Neural Phospho Signaling (RRID:SCR_023659) Copy   

•   Source: SciCrunch Registry

http://mouse.cs.ucla.edu/emma/

Statistical test for model organisms association mapping correcting for the confounding from population structure and genetic relatedness. EMMA takes advantage of the specific nature of the optimization problem in applying mixed models for association mapping, which substantially increases the computational speed and the reliability of the results. The current implementation of EMMA is available in an R package. The documentation is included in the installation package.

Proper citation: Efficient Mixed-Model Association (RRID:SCR_008217) Copy   

•   Source: SciCrunch Registry

http://med.stanford.edu/compmed/education/phd_training.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 27,2022.This program helps address the shortage of veterinarians who are trained for independent research. It supports veterinarians during the first 3 years of their PhD training. Trainees can participate in any graduate program involved in biomedical research at Stanford University: Biochemistry, Biological Sciences, Biophysics, Cancer Biology, Developmental Biology, Genetics, Immunology, Microbiology & Immunology, Molecular & Cellular Physiology, Molecular Pharmacology, Neurosciences, Structural Biology, Bioengineering, and Biomedical Informatics (graduate programs in biomedical research). All share common features: :1. Year 1 focuses on a limited group of courses and laboratory rotations. :2. Subsequent years focus on developing critical thinking via seminars and journal clubs and on independent research. :3. Annual retreats to present and learn about ongoing research in the graduate program. :4. Emphasis on mastering communications skills essential for success in science: oral presentation, writing manuscripts and grant proposals. :5. Developing an appreciation of the role of scientists in the context of society with emphasis on ethical and professional responsibility. Sponsors: It is funded by a T32 training grant from the NIH.

Proper citation: Postdoctoral Program for Veterinarians (RRID:SCR_008296) Copy   

•   Source: SciCrunch Registry

http://www.openbioinformatics.org/

An open bioinformatis software repository with no tie to any organization or institution. Contact them to host your software.

Proper citation: OpenBioinformatics.org (RRID:SCR_002229) Copy   

•   Source: SciCrunch Registry

https://neurophysics.ucsd.edu/software.php

Matlab-based routines for the detection and clustering of putative single units from a multi-unit time series, along with quality metrics. This sofwtare was developed by the David Kleinfeld Laboratory at UC San Diego.

Proper citation: UltraMegaSort 2000 (RRID:SCR_015857) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/icacompass/

Algorithm for MATLAB and the EEGLAB toolbox that enables the automatic detection of independent components from an ICA that represent event-related brain potentials. It performs automatic Independent Component (IC) selection with respect to the contributions of the ICs to a certain ERP.

Proper citation: COMPASS (RRID:SCR_015874) Copy   

•   Source: SciCrunch Registry

https://github.com/NuttyLogic/EpigeneticPacemaker

Python implementation of conditional expectation maximization algorithm that estimates epigenetic landscapes and state of individuals and may be used to study nonlinear epigenetic aging. Fast conditional expectation maximization algorithm used to model epigenetic states associated with phenotype of interest. Can model non linear epigenetic trait associations directly without transformation of phenotype of interest.

Proper citation: Epigenetic Pacemaker (RRID:SCR_018158) Copy   

•   Source: SciCrunch Registry

http://gps.biocuckoo.org/

Software that detects kinase-specific phosphorylation sites. GPS provides a platform able to perform its prediction based on a group-based phosphorylation scoring algorithm. It allows users to query multiple protein sequences through a batch prediction mode.

Proper citation: GPS (RRID:SCR_016374) Copy   

•   Source: SciCrunch Registry

http://huttenhower.sph.harvard.edu/galaxy

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Algorithm for high-dimensional biomarker discovery and explanation that identifies genes, pathways, or taxa characterizing the differences between two or more biological conditions. The algorithm identifies features that are statistically different among biological classes, then performs additional tests to assess whether these differences are consistent with respect to expected biological behavior. Statistical significance and biological relevance are emphasized., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: LEfSe (RRID:SCR_014609) Copy   

•   Source: SciCrunch Registry

https://edspace.american.edu/openbehavior/

Repository of open source tools for behavioral neuroscience research. OpenBehavior features hardware (tools, devices, apparatuses), as well as software for data acquisition and analysis and for the investigation of animal behavior and cognition. Dedicated to accelerating research through promotion of collaboration and open source projects.

Proper citation: OpenBehavior (RRID:SCR_015938) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=Boruta

Algorithm that performs feature selection. It finds relevant features by comparing original attributes' importance with importance achievable at random, estimated using their permuted copies (shadows).

Proper citation: Boruta (RRID:SCR_016234) Copy   

•   Source: SciCrunch Registry

https://code.gov/

Code repository for all government funded software. Designed to support reuse and public access to custom developed Federal source code. It requires new custom developed source code developed specifically by or for Federal Government to be made available for sharing and re-use across all Federal agencies. Provides tools to help government and public collaborate on open source projects.

Proper citation: code.gov (RRID:SCR_017601) Copy   

•   Source: SciCrunch Registry