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http://www.bscs.org/science-mental-illness

A set of lessons for students used to gain insight into the biological basis of mental illnesses and how scientific evidence and research can help us understand its causes and lead to treatments and, ultimately, cures. Both the Web version and the free supplement are available. It is a creative, inquiry-based instruction program designed to promote active learning and stimulate student interest in medical topics. This curriculum supplement aims to help students experience the process of scientific inquiry and develop an enhanced understanding of the nature and methods of science.

Proper citation: Science of Mental Illness: Grades 6- 8 (RRID:SCR_005612) Copy   

•   Source: SciCrunch Registry

http://www.genexplain.com/

An online toolbox and workflow management system for a broad range of bioinformatic and systems biology applications. The individual modules, or Bricks, are unified under a standardized interface, with a consistent look-and-feel and can flexibly be put together to comprehensive workflows. The workflow management is intuitively handled through a simple drag-and-drop system. With this system, you can edit the predefined workflows or compose your own workflows from scratch. Your own Bricks can easily be added as scripts or plug-ins and can be used in combination with pre-existing analyses. GeneXplain GmbH provides a number of state-of-the-art bricks; some of them can be obtained free of charge, while others require licensing for small fee in order to guarantee active maintenance and dynamic adaptation to the rapidly developing know-how in this field.

Proper citation: geneXplain (RRID:SCR_005573) Copy   

•   Source: SciCrunch Registry

http://bioinfo.unice.fr/

Virtual Biology Lab portal from the University of Nice Sophia Antipolis; Nice; France. Offered are a variety of software including: * GenBank2Treedyn: Extract annotations from GenBank files for: ** More convenient alignments and phylogeny (replace def line of fasta file by GI number) ** Extremely powerful annotations of phylogenetic trees with TreeDyn. * THEA: Analyses of DNA chip data with ontologies * Blast2Tree: Blast server for the identification of procaryotes * Dashboard: e-Tool for data exchanges among partners, DNA chips design and developement * Oligo Heat Map: Check thermodynamical parameters for PCR primers and compute graphical representation to show specificity of target sequences * EmblEx: A cgi tool to parse and extract data from EMBL entries to various formats * Miscellaneous software ** Jane plugin: Add a small panel to Jane server to retrieve PMID of publications ** EtBlast plugin: Add a small panel to EtBlast server to retrieve PMID of publications ** Oligo Builder: Get the oligomers from a set of target sequences by avoiding non-target sequences

Proper citation: Virtual Biology Lab (RRID:SCR_005694) Copy   

•   Source: SciCrunch Registry

https://biit.cs.ut.ee/

The Bioinformatics, Algorithmics, and Data Mining group BIIT lead by prof. Jaak Vilo is a joint research group between the Department of Computer Science (University of Tartu), Quretec, and the Estonian Biocenter. Our main research topics and capabilities include the gene regulation, gene expression data analysis, biological data mining, systems biology, combinatorial pattern matching, developing software for biomedical research databases, as well as partnering in stem cell and cancer related projects. Software * MEM - Multi-Experiment-Matrix -- large-scale gene expression data queries and mining (Genome Biology 2009) * g:Profiler family of tools for functional assessment of gene groups, gene ID mappings, orthology and expression similarity searches. (NAR web server issue 2007) * KEGGanim - visualisation of high-throughput data on biological pathway charts (Bioinformatics, 2007) * GraphWeb - a tool for mining large biological networks (NAR Web server issue 2008) * FunGenES data atlas * More software tools

Proper citation: BIIT - Bioinformatics Algorithmics and Data Mining Group (RRID:SCR_005690) Copy   

•   Source: SciCrunch Registry

http://bioinfo.cipf.es/

Biomedicine can only be understood in the context of genomics and with the concourse of bioinformatics. Our department aims to tackle biomedical problems from a system's biology perspective. Following this, the general objective we seek through the main lines of research is to relate the mutations (Pharmacogenomics and Comparative Genomics) to their effect at cellular and phenotypic level (Functional Genomics) trying to understand the mechanism of action (Structural Genomics). Systems Biology Genes operate within an intricate network of interactions that we have only recently started to envisage. Many higher-order levels of interaction are continuously being discovered. In this scenario we are interested in developing methods and tools which can help to understand large-scale experiments from a systems biology perspective. Comparative genomics We are interested in the analysis of patterns and processes occurred during the evolution of our genome, and in the application of the evolutionary thought in human health and disease. * Adaptive Human Evolution * Evolutionary Pharmacogenetics * SNP's and Human Disease Structural genomics Our Unit aims to develop and apply computational methods for understanding the molecular mechanisms of cell regulation beyond proteins. In particular, we apply our methods to study the interaction of small chemical compounds with proteins and to characterize their molecular actions. We are also developing methods for RNA 3D structure prediction with the aim of applying them to understand the effects of non-coding RNA molecules. Finally, in collaboration with experimentalists, we are working in determining the first ever 3D structure of a genomic domain in human.

Proper citation: CIPF Bioinformatics and Genomics Department (RRID:SCR_005692) Copy   

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http://bioportal.bioontology.org/annotator

A Web service that annotates textual metadata (e.g. journal abstract) with relevant ontology concepts. NCBO uses this Web service to annotate resources in the NCBO Resource Index. They also provide this Web service as a stand-alone service for users. This Web service can be accessed through BioPortal or used directly in your software. Currently, the annotation workflow is based on syntactic concept recognition (using concept names and synonyms) and on a set of semantic expansion algorithms that leverage the semantics in ontologies (e.g., is_a relations). Their service methodology leverages ontologies to create annotations of raw text and returns them using semantic web standards.

Proper citation: NCBO Annotator (RRID:SCR_005329) Copy   

•   Source: SciCrunch Registry

http://www.nimh.nih.gov/educational-resources/brain-basics/brain-basics.shtml

Brain Basics provides information on how the brain works, how mental illnesses are disorders of the brain, and ongoing research that helps us better understand and treat disorders. Mental disorders are common. You may have a friend, colleague, or relative with a mental disorder, or perhaps you have experienced one yourself at some point. Such disorders include depression, anxiety disorders, bipolar disorder, attention deficit hyperactivity disorder (ADHD), and many others. Some people who develop a mental illness may recover completely; others may have repeated episodes of illness with relatively stable periods in between. Still others live with symptoms of mental illness every day. They can be moderate, or serious and cause severe disability. Through research, we know that mental disorders are brain disorders. Evidence shows that they can be related to changes in the anatomy, physiology, and chemistry of the nervous system. When the brain cannot effectively coordinate the billions of cells in the body, the results can affect many aspects of life. Scientists are continually learning more about how the brain grows and works in healthy people, and how normal brain development and function can go awry, leading to mental illnesses. Brain Basics will introduce you to some of this science, such as: * How the brain develops * How genes and the environment affect the brain * The basic structure of the brain * How different parts of the brain communicate and work with each other * How changes in the brain can lead to mental disorders, such as depression.

Proper citation: Brain Basics (RRID:SCR_005606) Copy   

•   Source: SciCrunch Registry

http://www.arabidopsis.org/servlets/Search?type=keyword&action=new_search

TAIR Keyword Browser searches and browses for Gene Ontology, TAIR Anatomy, and TAIR Developmental stage terms, and allows you to view term details and relationships among terms. It includes links to genes, publications, microarray experiments and annotations associated with the term or any children terms. Platform: Online tool

Proper citation: TAIR Keyword Browser (RRID:SCR_005687) Copy   

•   Source: SciCrunch Registry

http://services.nbic.nl/copub/portal/

Text mining tool that detects co-occuring biomedical concepts in abstracts from the MedLine literature database. It allows batch input of multiple human, mouse or rat genes and produces lists of keywords from several biomedical thesauri that are significantly correlated with the set of input genes. These lists link to Medline abstracts in which the co-occurring input genes and correlated keywords are highlighted. Furthermore, CoPub can graphically visualize differentially expressed genes and over-represented keywords in a network, providing detailed insight in the relationships between genes and keywords, and revealing the most influential genes as highly connected hubs.

Proper citation: CoPub (RRID:SCR_005327) Copy   

•   Source: SciCrunch Registry

http://202.97.205.78/CpG_MPs/

Tool for identification and analysis of CpG methylation patterns of genomic regions from high-throughput bisulfite sequencing data. It may identify the unmethylated and methylated regions for a single sample, the conserved and differential methylation regions with different methylation patterns for paired or multiple samples. It includes four main modules as follows: # Normalization of the sequencing reads of cytosines following guanines; # Identification of the unmethylated (methylated) regions using hotspot extension algorithm; # Identification of conservatively and differentially methylated regionsby combining the combinatorial algorithm for determination of potentially functional regions with the algorithm of analysis of variance (ANOVA) for assess the statistical significance of differentially methylated regions; # Extraction of sequence features and visualization of these potentially functional regions.

Proper citation: CpG MPs (RRID:SCR_005441) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gtr/

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://www.pandora.cs.huji.ac.il/

With PANDORA, you can search for any non-uniform sets of proteins and detect subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA supports GO annotations as well as additional keywords (from UniProt Knowledgebase, InterPro, ENZYME, SCOP etc). It is also integrated into the ProtoNet system, thus allowing testing of thousands of automatically generated protein families. Note that PANDORA replaces the ProtoGO browser developed by the same group. Platform: Online tool

Proper citation: Pandora - Protein ANnotation Diagram ORiented Analysis (RRID:SCR_005686) Copy   

•   Source: SciCrunch Registry

http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://www.biological-networks.org/pubs/suppl/sinomo/

Analysis-tool which identifies singular node motifs in a network. Network nodes can be described by node-motifs. It is an improvement to the method described in Costa et al. (2009).

Proper citation: SINOMO (RRID:SCR_005286) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/gofish/GoFishWelcome.html

Software program, available as a Java applet online or to download, allows the user to select a subset of Gene Ontology (GO) attributes, and ranks genes according to the probability of having all those attributes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GoFish (RRID:SCR_005682) Copy   

•   Source: SciCrunch Registry

http://en.wikibooks.org/wiki/MINC/Atlases

A linear average model atlas produced by the International Consortium for Brain Mapping (ICBM) project. A set of full- brain volumetric images from a normative population specifically for the purposes of generating a model were collected by the Montreal Neurological Institute (MNI), UCLA, and University of Texas Health Science Center at San Antonio Research Imaging Center (RIC). 152 new subjects were scanned using T1, T2 and PD sequences using a specific protocol. These images were acquired at a higher resolution than the original average 305 data and exhibit improved contrast due predominately to advances in imaging technology. Each individual was linearly registered to the average 305 and a new model was formed. In total, three models were created at the MNI, the ICBM152_T1, ICBM152_T2 and ICBM152_PD from 152 normal subjects. This resulting model is now known as the ICBM152 (although the model itself has not been published). One advantage of this model is that it exhibits better contrast and better definition of the top of the brain and the bottom of the cerebellum due to the increased coverage during acquisition. The entirely automatic analysis pipeline of this data also included grey/white matter segmentation via spatial priors. The averaged results of these segmentations formed the first MNI parametric maps of grey and white matter. The maps were never made publicly available in isolation but have formed parts of other packages for some time including SPM, FSL AIR and as models of grey matter for EEG source location in VARETTA and BRAINWAVE. Again, as these models are an approximation of Talairach space, there are differences in varying areas, to continue our use of origin shift as an example, the ICBM models are approximately 152: +3.5mm in Z and +-co-ordinate -3.5mm and 2.0mm in Y as compared to the original Talairach origin. In addition to the standard analysis performed on the ICBM data, 64 of the subjects data were segmented using model based segmentation. 64 of the original 305 were manually outlined and a resulting parametric VOI atlas built. The native data from these acquisitions was 256x256 with 1mm slices. The final image resolution of this data was 181x217x181 with 1mm isotropic voxels. Refer to the ICBM152 NonLinear if you are fitting an individual to model and do not care about left/right comparisons. A short history of the various atlases that have been produced at the BIC (McConnell Brain Imaging Center, Montreal Neurological Institute) is provided.

Proper citation: MINC/Atlases (RRID:SCR_005281) Copy   

•   Source: SciCrunch Registry

http://bioimage.ucsb.edu/bisque

Open source database for exchange and exploration of biological images. Used to store, visualize, organize and analyze images in cloud. Centered around database of images and metadata.

Proper citation: Bisque database (RRID:SCR_005559) Copy   

•   Source: SciCrunch Registry

http://www.yandell-lab.org/software/mwas.html

The MAKER Web Annotation Service (MWAS) is an easily configurable web-accessible genome annotation pipeline. It''''s purpose is to allow research groups with small to intermediate amounts of eukaryotic and prokaryotic genome sequence (i.e. BAC clones, small whole genomes, preliminary sequencing data, etc.) to independently annotate and analyze their data and produce output that can be loaded into a genome database. MWAS is build on the stand alone genome annotation pipeline MAKER, and users who wish to annotate larger datasets and whole genomes are free to download MAKER for use on their own systems. MWAS identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MWAS can also automatically train popular gene prediction algorithms for use on new genomes for which pre-existing information is limited. MAKER is a member of the Generic Model Organism Database (GMOD) project and output produced by this site can be directly used with other GMOD tools. Annotations can be directly viewed online by the user via GBrowse, JBrowse, and Apollo, or they can be downloaded for local analysis and integration into a genome database. MWAS also supplies summary statistics on sequence features via the Sequence Ontology tool SOBA. MWAS should prove especially useful for emerging model organism genome projects with minimal bioinformatics expertise and computer resources, since a user can produce final genome annotations without having to install and configure any software locally.

Proper citation: MAKER Web Annotation Service (RRID:SCR_005318) Copy   

•   Source: SciCrunch Registry

http://www.thehamner.org/technology-and-development/technology-transfer/index.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 24, 2013. BMDExpress is a Java application used to analyze dose-response data from microarray experiments. The program was designed to perform a stepwise analysis on microarray data that combines bench mark dose (BMD) calculations with gene ontology (GO) classification analysis. The combination provides dose estimates at which different cellular processes are altered at a defined increase in risk based on expression levels in the untreated controls. The fitting of the data to the statistical models (linear, 2 polynomial models, 3 polynomial, and power models) is performed using source code borrowed from the U.S. Environmental Protection Agency''''s BMDS software. The MPPD model is a computational model that can be used for estimating human and rat airway particle dosimetry. The model is applicable to risk assessment, research, and education. The MPPD model calculates the deposition and clearance of monodisperse and polydisperse aerosols in the respiratory tracts of rats and human adults and children (deposition only) for particles ranging in size from ultrafine (0.01 m) to coarse (20 m). The models are based on single-path and multiple-path methods for tracking air flow and calculating aerosol deposition in the lung. The single-path method calculates deposition in a typical path per airway generation, while the multiple-path method calculates particle deposition in all airways of the lung and provides lobar-specific and airway-specific information. Within each airway, deposition is calculated using theoretically derived efficiencies for deposition by diffusion, sedimentation, and impaction within the airway or airway bifurcation. Filtration of aerosols by the head is determined using empirical efficiency functions. The MPPD model includes calculations of particle clearance in the lung following deposition. Eight tutorials are provided so that the user can learn to interact with the software.

Proper citation: The Hamner Institute for Health Sciences: BMDExpress and The multiple-path particle dosimetry (RRID:SCR_005511) Copy   

•   Source: SciCrunch Registry

http://maq.sourceforge.net/maqview.shtml

A graphical read alignment viewer specifically designed for the Maq alignment file and allows you to see the mismatches, base qualities and mapping qualities. It is highly efficient in speed, memory and disk usage. Maqview is based on OpenGL and is known to work on both Mac OS X and Linux. Porting to Windows is in principle easy.

Proper citation: Maqview (RRID:SCR_005632) Copy   

•   Source: SciCrunch Registry