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http://psychiatry.ucsd.edu/Neuroembryologylab/index.htm

Dr. Eric Turner''s laboratory studies the mechanisms underlying the development of the nervous system. The vertebrate brain is comprised of a tremendous variety of neurons, each class exhibiting a unique phenotype characterized by the expression of specific neurotransmitter receptors, ion channels, patterns of axonal growth, and synapse formation. The research we conduct focuses on the critical role transcription factors play in the specification of neuronal cell type during development. We are particularly interested in transcription factors of the homeodomain family that bind to DNA and in doing so activate or repress gene expression. One area of study is the role of POU-domain transciption factor Brn3a in axon growth and survival. The primary research areas are: * Neuronal cell fate determination: The expression of regulatory genes is manipulated in living chick embryos using microsurgery and electroporation and the effects on neural marker genes studied. * Molecular mechanisms of gene regulation: Target DNA binding sites of neural transcription factors are biochemically characterized and findings coordinated with sequence data from the mouse and human genomes. * Targeted misexpression of regulatory genes: Transgenic and knockout mouse technology is used to misexpress genes of interest, and the effects on neural marker genes, axonal growth, and cell survival studied. * Global analysis of neural gene expression: Micro-arrays (GeneChips) are employed in conjunction with other areas of study to understand the coordinated regulation of gene expression in the nervous system. Dr. Turner is a member of the University of California, San Diego''s Graduate Program in Neuroscience and Biomedical Sciences Program and accepts students from these two programs. Interesting rotation projects are available using methods ranging from biochemistry and molecular biology to embryology. Additionally, Dr. Turner is also the Director of this NIMH-funded training program for research-oriented psychiatrists, psychologists, and basic neuroscientists working in areas relevant to psychiatry. Typically Fellows spend two years in the program, during which they develop a research project under the close supervision of one of the highly productive members of the UCSD Department of Psychiatry, or another investigator in the La Jolla (UCSD/Salk/Scripps) research community.

Proper citation: Department of Psychiatry, Turner Laboratory (RRID:SCR_008067) Copy   

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http://edge.oncology.wisc.edu/edge.php

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. EDGE is a scientific resource for toxicology-related gene expression information. The site contains databases and analyses of gene expression studies following exposure to a variety of chemicals or physiological changes. The ultimate goal of the EDGE is to map transcriptional changes from chemical exposure that will someday be used as a diagnostic fingerprint to predict toxicity as well as provide valuable insights into the basic molecular changes responsible. EDGE gives you the ability to easily answer the following fundamental questions about your data 1. Can I compare transcriptional profiles across treatments? 2. What genes respond to my treatment? 3. What influences my favorite gene(s)? One of the major objectives of toxicology is to understand the adverse health effects that result from exposure to foreign chemicals. The traditional method for assessing the toxicity of a test chemical is very resource intensive; requiring the commitment of large amounts of money, time, and animals. According to the National Toxicology Program (NTP), each chemical study requires between 2 and 4 million dollars and several years to complete. Due to the cost and labor intensive nature of these studies, the number of chemicals currently tested by the NTP stands at less than 500. Given these statistics and the fact that there are approximately 70,000 chemicals in commerce today, it is increasingly apparent that alternative methods for assessing toxic potential must be explored if a significant portion of the remaining chemicals is to be tested. One potential solution is to develop a comprehensive database that describes alterations in gene expression resulting from chemical exposure. The pattern of transcriptional activity will not only be highly sensitive indicator of chemical exposure, but that this pattern will be diagnostic for mechanistically linked toxicants. In our laboratory, we have chosen to address this problem through a combination of high throughput sequencing of expressed sequence tags (ESTs) and construction of custom toxicology-related cDNA microarrays derived from the unique ESTs identified in the sequencing effort. By using this approach, we can simultaneously develop a quantitative gene expression profile using ESTs and the reagents for further analyzing these changes in a rapid, highly parallel manner. In addition, the expression profiles are not biased for preselected favorite genes. The resulting gene expression pattern can then be used as diagnostic fingerprint to predict toxicity and/or carcinogenicity as well as provide valuable insight into the basic biochemical and molecular changes responsible for toxicity. Submission of total RNA for Bradfield Lab Microarray Microarray comparisons are made between untreated, control animals and animals treated with ONE treatment. Please make sure the RNA submitted adheres to this experimental design. Necessary information is available on the site.

Proper citation: EDGE: Environment, Drugs and Gene Expression (RRID:SCR_008187) Copy   

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http://inc.ucsd.edu/

The Institute for Neural Computation (INC) is an organized research unit of the University of California at San Diego with 44 members representing 14 research disciplines, devoted to the research and development of a new generation of massively parallel computers through a coherent and cohesive plan of research spanning the areas of neuroscience, visual science, cognitive science, artificial intelligence, mathematics, economics and social science, and computer engineering. INC is a leading center in the field of neural computation, initiating joint research projects, providing special facilities for carrying out research, coordinating the training of young investigators, and offering special activities through its Industrial Affiliates Program. The INC also supports training programs for graduate students and postdoctoral fellows in Cognitive Neuroscience (NIH) and Computational Neurobiology (NFS).

Proper citation: Institute for Neural Computation (RRID:SCR_008068) Copy   

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http://sig.biostr.washington.edu/projects/fm/FME/index.html

The Foundational Model Explorer (FME) is an internet based software application developed for viewing the content and organization of the Foundational Model of Anatomy Ontology (FMA). The initial purpose of the FME was to provide a simple and intuitive interface to the FMA for domain experts, in the field of anatomy, participating in the evaluation of the FMA. The FME also provides an easily available method of exploring the FMA to individuals or groups considering the adoption of the Foundational Model of Anatomy knowledge base. The FME display consists of two panes: a hierarchical tree may be opened up in the pane on the left side; if a class is selected in the hierarchical tree, the pane on the right side displays the information that has been entered in the FMA for that class. The information associated with a given class is organized in so-called slots. Each slot has a name (e.g., Definition, Parts) and some content, which is that particular slots value (e.g., the English definition and the names of parts of the selected class, respectively). For an explanation of the interactive features of the FME, see the Knowledge Navigation Section. For a guided tutorial check out the Conducted Tour. In the left pane, the default tree is a subclass hierarchy, based on the -is a- or -kind of- relationship; it is the instantiation of the Anatomy taxonomy (At) component in the high level scheme of the Foundational Model of Anatomy. Apart from the slots Preferred Name and Synonyms, other slots relate to the Anatomical Structural Abstraction (ASA) component in the FMAs high level scheme. Hierarchies based on various part-whole relationships can also be opened up in the left pane. Once a class has been highlighted in the subclass hierarchy, you can choose a relationship from a drop down list labeled Select navigation tree type. Some other transitive relationships (e.g., -branch of- and -tributary of-) are also available. The Search facility matches a search term to the preferred name, as well as to the Latin name, or synonym of an FMA class (if such exist). The tree is expanded to reveal the matching class and the information about this class is displayed. The wildcard * is allowed in the search term and will match to any sequence of characters. For example the search term h*d matches the class names Head and Hepatic cord (amongst others). The search function is not case sensitive. If more than one class name matches with the search term, a list of matching terms is presented for the user to choose between.

Proper citation: Foundational Model Explorer (RRID:SCR_008189) Copy   

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http://genewindow.nci.nih.gov/

Software tool for pre- and post-genetic bioinformatics and analytical work, developed and used at the Core Genotyping Facility (CGF) at the National Cancer Institute. While Genewindow is implemented for the human genome and integrated with the CGF laboratory data, it stands as a useful tool to assist investigators in the selection of variants for study in vitro, or in novel genetic association studies. The Genewindow application and source code is publicly available for use in other genomes, and can be integrated with the analysis, storage, and archiving of data generated in any laboratory setting. This can assist laboratories in the choice and tracking of information related to genetic annotations, including variations and genomic positions. Features of GeneWindow include: -Intuitive representation of genomic variation using advanced web-based graphics (SVG) -Search by HUGO gene symbol, dbSNP ID, internal CGF polymorphism ID, or chromosome coordinates -Gene-centric display (only when a gene of interest is in view) oriented 5 to 3 regardless of the reference strand and adjacent genes -Two views, a Locus Overview, which varies in size depending on the gene or genomic region being viewed and, below it, a Sequence View displaying 2000 base pairs within the overview -Navigate the genome by clicking along the gene in the Locus Overview to change the Sequence View, expand or contract the genomic interval, or shift the view in the 5 or 3 direction (relative to the current gene) -Lists of available genomic features -Search for sequence matches in the Locus Overview -Genomic features are represented by shape, color and opacity with contextual information visible when the user moves over or clicks on a feature -Administrators can insert newly-discovered polymorphisms into the Genewindow database by entering annotations directly through the GUI -Integration with a Laboratory Information Management System (LIMS) or other databases is possible

Proper citation: GeneWindow (RRID:SCR_008183) Copy   

•   Source: SciCrunch Registry

http://www.utsa.edu/claibornelab/

The long-term goals of my research are to understand the relationship between neuronal structure and function, and to elucidate the factors that affect neuronal morphology and function over the lifespan of the mammal. Currently we are examining 1) the effects of synaptic activity on neuronal development; 2) the effects of estrogen on neuronal morphology and on learning and memory; and, 3) the effects of aging on neuronal structure and function. We have focused our efforts on single neurons in the hippocampal formation, a region that is critical for certain forms of learning and memory in rodents and humans. From the portal, you may click on a cell in your region of interest to see the complete database of cells from that region. You may also explore the Neuron Database: * Comparative Electrotonic Analysis of Three Classes of Rat Hippocampal Neurons. (Raw data available) * Quantitative, three-dimensional analysis of granule cell dendrites in the rat dentate gyrus. * Dendritic Growth and Regression in Rat Dentate Granule Cells During Late Postnatal Development.(Raw data available) * A light and electron microscopic analysis of the mossy fibers of the rat dentate gyrus.

Proper citation: University of Texas at San Antonio Laboratory of Professor Brenda Claiborne (RRID:SCR_008064) Copy   

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http://www.cambridgesoft.com/databases/login/?serviceid=128

THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. ChemBioFinder.com is an online chemistry and biology reference database. With more than 500,000 compounds indexed and linked to other web sites, it provides a wealth of chemical information for professional chemists and students alike. ChemBioFinder.com is the gateway to all databases available from CambridgeSoft.
At ChemBioFinder.com, a subscriber can search for compounds by name, CAS Registry Number, molecular formula or weight, or by structure (exact and substructure). Successful searches return a basic profile of molecules indexed by this site. The profile contains the name, molecular formula and weight, CAS Registry Number, SMILES and InChI strings for each located compound, and lists the databases which contain entries for the located compound(s). Free trials to any of these databases are available, as are annual subscriptions for continuous use of the contents.
Users of ChemBioFinder.com are allowed 5 free searches before we request them to register with us as a cambridgesoft.com website user. The CambridgeSoft user account is free and will give you access to a growing list of products and services which includes, our quarterly print publication Chem & Bio News, frequent webinars, white papers and articles on all our offerings. Set up is fast & easy.
For ChemFinder.com users:
ChemFinder.Com has become ChemBioFinder.Com and has a whole new look and layout. This is part of a gradual redesign of the entire CambridgeSoft website. Here are some of the changes that were made to improve the vital information presented here to the scientific community:
1. Search results show the ChemBioFinder databases which have entries for the compound(s), and indicate the databases to which the logged in user has active subscriptions.
2. There are hyperlinks to the detailed records in the databases with active subscriptions.
3. Search results provide the name, molecular formula and weight, CAS Registry Number, SMILES and InChI strings for the compound.
4. Physical properties are no longer provided unless the user has a subscription to ChemIndex or other CambridgeSoft online databases that provide this information. Many of our products come with one year subscriptions to ChemIndex as part of the package. So you may actually be entitled to a subscription and dont realize it.

Proper citation: ChemBioFinder (RRID:SCR_008180) Copy   

•   Source: SciCrunch Registry

http://www.hopkins-abxguide.org/

Concise, clinically useful information for diagnosing, managing and treating infectious diseases in adults; however it does cover some pediatric topics including vaccines. It is designed for primary care providers and other non-infectious disease specialists as a tool that can be used at the point of care to assist in prescribing antibiotics.

Proper citation: ABX Guide (RRID:SCR_008214) Copy   

•   Source: SciCrunch Registry

http://sys-bio.org/downloads/

An open source framework for systems biology connecting heterogeneous software applications written in diverse programming languages and running on different platforms-to communicate and use each others'' capabilities via a fast binary encoded-message system. It uses a broker-based, distributed, message-passing architecture, supports many languages including Java, C++, Perl & Python, and runs under Linux,OSX & Win32. Many biological modeling and simulation tools are a part of SBW, including JDesigner and Jarnac.

Proper citation: Systems Biology Workbench (RRID:SCR_008059) Copy   

•   Source: SciCrunch Registry

http://nsdl.org/

NSDL is a digital library of exemplary resource collections and services, organized in support of science education at all levels. Starting with a partnership of NSDL-funded projects, NSDL is emerging as a center of innovation in digital libraries as applied to education, and a community center for groups focused on digital-library-enabled science education. The National Science Digital Library (NSDL) was created by the National Science Foundation to provide organized access to high quality resources and tools that support innovations in teaching and learning at all levels of science, technology, engineering, and mathematics (STEM) education. As a national network of learning environments, resources, and partnerships, NSDL seeks to serve a vital role as STEM educational cyberlearning for the nation, meeting the informational and technological needs of educators and learners at all levels. Educators need efficient and reliable methods to discover and use science and math materials that help them meet the demands of instruction, assessment, and professional development in an increasingly complex technology-based world. NSDL provides an organized point of access to: -High-quality STEM content aggregated from a variety of other digital libraries, NSF-funded projects, and NSDL-reviewed web sites. -Services and tools that enhance the use of this content in a variety of contexts. NSDL is designed primarily for K-16 educators, but anyone can access NSDL.org and search the library at no cost. Access to most resources discovered through NSDL is free; however, some content providers may require a login, or a nominal fee or subscription to retrieve their specific resources. NSDL serves as a nexus for educators, researchers, policy makers and the public by building bridges: -Between private sector and public interests by providing access to resources such as publisher'' journal articles, teacher-created lesson plans and real-time data sets from scientists -Between the scientific, research and educational communities by applying advanced technologies to stimulate new ways for educators and learners to access and use scientific information -Between teachers and learners at all levels, in all locations by supplying content and tools in open-access, non-proprietary formats in an easily accessible online environment. Sponsors: This work supported by the National Science Foundation under Grant No. 0733600, Grant No. 0424671, Grant No. 0227648, Grant No. 0227656, and Grant No. 0227888.

Proper citation: NSDL: The National Science Digital Library (RRID:SCR_008215) Copy   

•   Source: SciCrunch Registry

http://www.sheffield.ac.uk/

Founded in 1905, the University of Sheffield is one of the UK''s leading Russell Group universities with an outstanding record in both teaching and research.

Proper citation: University of Sheffield; South Yorkshire; United Kingdom (RRID:SCR_008056) Copy   

•   Source: SciCrunch Registry

http://www.snl.salk.edu/~jude/neuron_exchange/

This resource contains to MATLAB code to make and show videos that can be acquired for free. Data for the movies came from a Macaque attention task. Data on this page came from the multiple-object tracking attention task in a Macaque: The monkeys fixated the white dot at the center of the computer monitor, and four striped stimuli appeared. Their eye position was monitored using an IR camera. The red cross shows where the eyes were pointing throughout each trial. The circle shows the location of the receptive field of the neuron under study during the recording. At the beginning of each trial, either one or two of the stimuli were highlighted, indicating to the monkey that they were the targets of attention. The stimuli then moved to new locations and paused, with one stimulus in the receptive field. After a brief pause, they moved to new locations and the fixation point disappeared. The monkey was rewarded with juice if it then looked at the cued targets. Attention Dask Demo (Avi File) contains Matlab code to make and show movies. Publication from this Dataset: * Differential attention-dependent response modulation across cell classes in macaque visual area V4. JF Mitchell, KA Sundberg, JH Reynolds. Neuron, 2007, 55. 131-141. * Supplemental Material, Neuron, 2007, 55. 131-141. :A Subset of data can be downloaded with analysis routines (easiest to download whole set with full subdirectory structure). Additionally, neuron data files can also be downloaded. :* Routines for Fano Factor, Autocorrelation, and Power Spectra (poster above): :o Plots Spike Waveform and Tests if Significant Visual Response: basic_info.m :o Firing Rate and Fano Factor Analysis (Mitchell et. al, 2007): rate_fano_psth.m :* Routines for Spike-LFP Coherence: :o Spike-LFP Coherence with Rate Normalization (attempting Womelsdorf & Fries, Cosyne, 2008): rate_normalized_coherence.m Sponsors: This work was supported by a grant from the National Eye Institute (EY016161, J.F.M. and J.H.R.), a National Institutes of Health Training Fellowship (J.F.M.), and a National Science Foundation Graduate Research Fellowship (K.A.S.).

Proper citation: Salk Institute for Biological Studies: Jude Mitchells Neuron Exchange and Matlab Analysis (RRID:SCR_008055) Copy   

•   Source: SciCrunch Registry

http://drive5.com/usearch/manual/uchime_algo.html

An algorithm for detecting chimeric sequences.

Proper citation: UCHIME (RRID:SCR_008057) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/funding/clinical-trials-for-researchers/practical/stard/index.shtml

A nationwide public health clinical trial conducted to determine the effectiveness of different treatments for people with major depression, in both primary and specialty care settings, who have not responded to initial treatment with an antidepressant. This is the largest and longest study ever done to evaluate depression treatment. The study is completed and no longer recruiting participants. Each of the four levels of the study tested a different medication or medication combination. The primary goal of each level was to determine if the treatment used during that level could adequately treat participants����?? major depressive disorder (MDD). Those who did not become symptom-free could proceed to the next level of treatment. The design of the STAR*D study reflects what is done in clinical practice because it allowed study participants to choose certain treatment strategies most acceptable to them and limited the randomization of each participant only to his/her range of acceptable treatment strategies. No prior studies have evaluated the different treatment strategies in broadly defined participant groups treated in diverse care settings. Over a seven-year period, the study enrolled 4,041 outpatients, ages 18-75 years, from 41 clinical sites around the country, which included both specialty care settings and primary medical care settings. Participants represented a broad range of ethnic and socioeconomic groups. All participants were diagnosed with MDD, were already seeking care at one of these sites, and were referred to the trial by their doctors. * STAR*D Study Medications: Citalopram (Celexa), Sertraline (Zoloft), Bupropion SR (Wellbutrin SR), Venlafaxine XR (Effexor XR), Buspirone (BuSpar), Mirtazapine (Remeron), Triiodothyronine (T3) (Cytomel), Nortriptyline (Pamelor, Aventyl), Tranylcypromine (Parnate), Lithium (Eskalith, Lithobid) *STAR*D Talk Therapy:Cognitive Therapy

Proper citation: Sequenced Treatment Alternatives to Relieve Depression Study (RRID:SCR_008051) Copy   

•   Source: SciCrunch Registry

http://openwetware.org/wiki/Main_Page

OpenWetWare is an effort to promote the sharing of information, know-how, and wisdom among researchers and groups who are working in biology & biological engineering. OWW provides a place for labs, individuals, and groups to organize their own information and collaborate with others easily and efficiently. In the process, the hope is that OWW will not only lead to greater collaboration between member groups, but also provide a useful information portal to our colleagues, and ultimately the rest of the world. OWW''s approaches to achieve their goals: # Lower the technical barriers to sharing and dissemination of knowledge in biological research # Build a community of researchers in biology and biological engineering that values, practices, and innovates the open sharing of information # Integrate OpenWetWare into existing and future reward structures in research

Proper citation: OpenWetWare (RRID:SCR_008053) Copy   

•   Source: SciCrunch Registry

http://qiime.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.

Proper citation: QIIME (RRID:SCR_008249) Copy   

•   Source: SciCrunch Registry

http://www.jax.org/imr/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 08, 2012. The function of the IMR is to select, import, cryopreserve, maintain, and distribute these important strains of mice to the research community. To improve their value for research, the IMR also undertakes genetic development of stocks, such as transferring mutant genes or transgenes to defined genetic backgrounds and combining transgenes and/or targeted mutations to create new mouse models for research. The function of the IMR is to: * select biomedically important stocks of transgenic, chemically induced, and targeted mutant mice * import these stocks into the Jackson Laboratory by rederivation procedures that rid them of any pathogens they might carry * cryopreserve embryos from these stocks to protect them against accidental loss and genetic contamination * backcross the mutation onto an inbred strain, if necessary * distribute them to the scientific community More than 1000 mutant stocks have been accepted by the IMR from 1992 through December 2006. Current holdings include models for research on cancer; breast cancer; immunological and inflammatory diseases; neurological diseases; behavioral, cardiovascular and heart diseases; developmental, metabolic and other diseases; reporter (e.g., GFP) and recombinase (e.g., cre/loxP) strains. About eight strains a month are being added to the IMR holdings. Research is being conducted on improved methods for assisted reproduction and speed congenic production. Most of the targeted mutants arrive on a mixed 129xC57BL/6 genetic background, and as many of these as possible are backcrossed onto an inbred strain (usually C57BL/6J). In addition, new mouse models are being created by intercrossing carriers of specific transgenes and/or targeted mutations. Simple sequence length polymorphism DNA markers are being used to characterize and evaluate differences between inbred strains, substrains, and embryonic stem cell lines.

Proper citation: Induced Mutant Resource (RRID:SCR_008366) Copy   

•   Source: SciCrunch Registry

http://www.osc.riken.jp/english/

Omics Science Center is aiming to develop a comprehensive system called Life Science Accelerator(LSA) for the advancement of omics research. The LSA is a comprehensive system consists of biological resources, human resources, technologies, know-how, and essential administrative ability. Ultimate goal of LSA is to support and accelerate the advancement in life science research. Omics is the comprehensive study of molecules in living organisms. The complete sequencing of genomes (the complete set of genes in an organism) has enabled rapid developments in the collection and analysis of various types of comprehensive molecular data such as transcriptomes (the complete set of gene expression data) and proteomes (the complete set of intracellular proteins). Fundamental omics research aims to link these omics data to molecular networks and pathways in order to advance the understanding of biological phenomena as systems at the molecular level.

Proper citation: RIKEN Omics Science Center (RRID:SCR_008241) Copy   

•   Source: SciCrunch Registry

http://www.repairgenes.org/index.shtml

The aim of the repairGenes site is to be a source of information about DNA repair genes and a useful resource for research on DNA repair. At the moment, the site contains information about a number of DNA repair genes from a set of selected species. The information is organized by organism and by biological process term as defined by the Gene Ontology (GO) project. The coverage of DNA repair genes is not complete, but hopefully it satisfies to demonstrate the concept and generate ideas for future versions of the system. At present, the raw data about DNA repair genes is extracted from the SWISS-PROT database, and categorized using the GO system. SWISS-PROT entries are being annotated by the Gene Ontology Annotation project at EBI. GOA is an ongoing project which will become more complete with time. As more data is released, this will be fed into repairGenes to keep it up-to-date. In future versions, the user will be able to search freely among organisms and categories of repair genes, enabling easy comparisons between species. For a taste of this, please have a look at the overview of repair genes from five major organisms. The amount of information in the system will be increased and the quality will be improved in the future. So will the features of the system.

Proper citation: repairGenes (RRID:SCR_008240) Copy   

•   Source: SciCrunch Registry

http://www.reciprocalnet.org/

Database of crystallographic information. Its membership includes crystallographic service facilities (that analyze crystals submitted by research chemists) located at major universities. These labs analyze anywhere from a few dozen to several hundred molecular structures each year and post the data online for the public to access. A distributed database engine takes care of shuttling this data across the Internet so that every structure can be located by the search engine. There may be a delay of a year or more between the time a structure is first analyzed and the time it finally becomes available for the public to see. This is due to intellectual property issues - the intervening time allows the chemists who first discovered the structure to publish it in a trade journal.

Proper citation: Reciprocal Net (RRID:SCR_008238) Copy   

•   Source: SciCrunch Registry