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http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

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http://www.ebi.ac.uk/intact

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

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http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

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http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

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http://bioinformatics.albany.edu/~dmaps

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. DMAPS database contains pre-computed multiple structure alignments for protein chains in the Protein Data Bank (PDB). Automated structure alignments have been generated for classified protein families using CE-MC algorithm. Alignments have been built only for those families with at least three members. Currently, multiple structure alignments are available for 3050 SCOP-, 3087 CATH-, 664 ENZYME- and 1707 CE-based families. Users will be able to retrieve multiple alignments for a given PDB chain classified by one of these criteria.

Proper citation: DMAPS - A Database of Multiple Alignments for Protein Structures (RRID:SCR_007140) Copy   

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http://www.biomanta.org/

This project encompasses development of novel biological network analysis methods and infrastructure for querying biological data in a semantically-enabled format, and aims to create a semantic interactome model. Research within the BioMANTA project will focus on computational modelling and analysis, primarily using Semantic Web technologies and Machine Learning methods, of large-scale protein-protein interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression, and subcellular localization and disease state attributes will be included in the resulting data model. Protein interactions are a fundamental component of biological processes. Many proteins are functional only in multimeric complexes, or require interaction partners to achieve their correct localisation or function. For this reason, the study of protein-protein interaction (PPI) networks has become an area of growing interest in computational biology. Through the use of Semantic Web technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL), interaction data is modelled to create a knowledge representation in which meaning is vested in the ontology rather than instances of data. Stochastic and computational intelligence methods are applied to this data to infer high coverage networks. Semantic inferencing is used to infer previously unknown and meaningful pathways. Major project components: - The BioMANTA Ontology:- An OWL DL ontology incorporating the PSI-MI Ontology, the NCBI Taxonomy, and elements of BioPax ontology and Gene Ontology (describing subcellular localisation). This allows us to re-use existing ontologies, thereby reducing overheads associated with knowledge acquisition in the ontology development process. We are able to integrate existing public data that contain annotation in these formats. - Data conversion & semantic protein integration:- A set of software components that convert protein-protein databases (DIP, MPact, IntAct, etc.) from PSI-MI XML to RDF compliant with the BioMANTA ontology. These software allow us to make these protein-protein interaction datasets (and more generally, any PSI-MI XML data) semantically available for querying and inference within BioMANTA. - A RDF triple store based on RDF Molecules and the MapReduce architecture:- A proof-of-concept RDF triple store using RDF molecules and Hadoop scale-out architectures. Regular RDF graphs are deconstructed into RDF molecules, which are distributed over distributed compute nodes in the MapReduce architecture, and are subsequently combined to form equivalent RDF graphs. Such an approach makes the distributed SPARQL querying and reasoning on RDF triple stores possible. - A quantitative framework to integrate networks extracted from independent data sources (gene expression, subcellular localization, and ortholog mapping):- The model is multi-layer, with a first layer based on Decision Trees where each Decision tree is built on each dataset independently. The tree nodes are cut using Shannon''s entropy (mutual information); the decision of these independent trees is integrated using logistic regression, and the parameters are optimised using maximum likelihood. Sponsors: This resource is supported by the Pfizer Global Research and Development, the Institute for Molecular Bioscience (IMB), and the University of Queensland, Australia.

Proper citation: BioMANTA (RRID:SCR_007177) Copy   

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http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

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http://bioinfo.pl/

This service offers a gateway to well-benchmarked protein structure and function prediction methods. Structural models collected from the prediction servers are assessed using the powerful 3D-jury consensus approach. The Structure Prediction Meta Server provides access to various fold recognition, function prediction and local structure prediction methods. The Server takes the amino acid sequence of the query protein, the reference name for the prediction job, and the E-mail address as input. The E-mail address is used only for notification about errors during the execution of the job. The query sequence and the reference name are placed in the process queue. The Meta Server accepts only sequences, which have not been submitted before. In case of duplicate sequences the second user will be notified with a link to the previous submission. Sequences longer than 800 amino acids are not accepted by some services. The internal SQL database offers the possibility to find any previous jobs processed by the Meta Server using regular expressions addressing field like E-mail, Job Name and the host name, from which the job was initiated. Each server has its own process queuing system managed by the Meta Server. All results of fold recognition servers are translated into uniform formats. The information extracted from the raw output of the servers includes the PDB codes of the hits, the alignments and the similarity (reliability) scores specific for every server. Mapping of the hits to the SCOP and FSSP classifications are made either using known PDB representatives or alignment of the template sequence with the databases of proteins in both classifications. The secondary structure assignments for all hits are taken from the mapped FSSP (red for helices and blue for strands). Underscored amino acids indicate the first residue after an insertion in the template sequence. The Meta server provides translation of the alignments in standard formats like FASTA, PDB or CASP. The Meta Server is coupled to consensus servers. They provide jury predictions based on the results collected from other services. Not all fold recognition servers are used by the jury system. The data stored on the meta server is available through http://meta.bioinfo.pl/data/JOBID/. Jobs older than 2 months are not shown. The Meta Server is only a set of programs aimed to process and manage biological data, while the predictive power of the service comes from (mostly) remote prediction providers. Sponsors: This resource is supported by The BioInfoBank Institute.

Proper citation: BioInfoBank Meta Server (RRID:SCR_007181) Copy   

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https://cgc.umn.edu

Center that acquires, maintains, and distributes genetic stocks and information about stocks of the small free-living nematode Caenorhabditis elegans for use by investigators initiating or continuing research on this genetic model organism. A searchable strain database, general information about C. elegans, and links to key Web sites of use to scientists, including WormBase, WormAtlas, and WormBook are available.

Proper citation: Caenorhabditis Genetics Center (RRID:SCR_007341) Copy   

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http://www.ccp4.ac.uk/

Portal for Macromolecular X-Ray Crystallography to produce and support an integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography, and other biophysical techniques. Used in the education and training of scientists in experimental structural biology for determination and analysis of protein structure.

Proper citation: CCP4 (RRID:SCR_007255) Copy   

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http://senselab.med.yale.edu/ordb/

Database of vertebrate olfactory receptors genes and proteins. It supports sequencing and analysis of these receptors by providing a comprehensive archive with search tools for this expanding family. The database also incorporates a broad range of chemosensory genes and proteins, including the taste papilla receptors (TPRs), vomeronasal organ receptors (VNRs), insect olfaction receptors (IORs), Caenorhabditis elegans chemosensory receptors (CeCRs), and fungal pheromone receptors (FPRs). ORDB currently houses chemosensory receptors for more than 50 organisms. ORDB contains public and private sections which provide tools for investigators to analyze the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide. The database aims to house all of the known olfactory receptor and chemoreceptor sequences in both nucleotide and amino acid form and serves four main purposes: * It is a repository of olfactory receptor sequences. * It provides tools for sequence analysis. * It supports similarity searches (screens) which reduces duplicate work. * It provides links to other types of receptor information, e.g. 3D models. The database is accessible to two classes of users: * General public www users have full access to all the public sequences, models and resources in the database. * Source laboratories are the laboratories that clone olfactory receptors and submit sequences in the private or public database. They can search any sequence they deposited to the database against any private or public sequence in the database. This user level is suited for laboratories that are actively cloning olfactory receptors.

Proper citation: Olfactory Receptor DataBase (RRID:SCR_007830) Copy   

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http://gene3d.biochem.ucl.ac.uk/Gene3D/

A large database of CATH protein domain assignments for ENSEMBL genomes and Uniprot sequences. Gene3D is a resource of form studying proteins and the component domains. Gene3D takes CATH domains from Protein Databank (PDB) structures and assigns them to the millions of protein sequences with no PDB structures using Hidden Markov models. Assigning a CATH superfamily to a region of a protein sequence gives information on the gross 3D structure of that region of the protein. CATH superfamilies have a limited set of functions and so the domain assignment provides some functional insights. Furthermore most proteins have several different domains in a specific order, so looking for proteins with a similar domain organization provides further functional insights. Strict confidence cut-offs are used to ensure the reliability of the domain assignments. Gene3D imports functional information from sources such as UNIPROT, and KEGG. They also import experimental datasets on request to help researchers integrate there data with the corpus of the literature. The website allows users to view descriptions for both single proteins and genes and large protein sets, such as superfamilies or genomes. Subsets can then be selected for detailed investigation or associated functions and interactions can be used to expand explorations to new proteins. The Gene3D web services provide programmatic access to the CATH-Gene3D annotation resources and in-house software tools. These services include Gene3DScan for identifying structural domains within protein sequences, access to pre-calculated annotations for the major sequence databases, and linked functional annotation from UniProt, GO and KEGG., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Gene3D (RRID:SCR_007672) Copy   

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http://www.dnaftb.org/dnaftb/

An animated primer on the basics of DNA, genes, and heredity organized around three key concepts: Classical Genetics, Molecules of Genetics, and Genetic Organization and Control. The science behind each concept is explained by: animation, image gallery, video interviews, problem, biographies, and links.

Proper citation: DNA From The Beginning: AN Animated Primer on the Basics of DNA, Genes, and Heredity (RRID:SCR_008028) Copy   

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http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

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http://pmd.ddbj.nig.ac.jp/

It provides information on natural and artificial mutants, including random and site-directed ones, for all proteins except members of the globin and immunoglobulin families. The PMD is based on literature, and each entry in the database corresponds to one article which may describe one, several or a number of protein mutants. Each database entry is identified by a serial number and is defined as either natural or artificial, depending on the type of the mutation. For each entry the following are recorded : JOURNAL, TITLE, CROSS-REFERENCE, PROTEIN, N-TERMINAL, CHANGE, FUNCTION, STRUCTURE, STABILITY, etc. CROSS-REFERENCE indicates the code names of the protein given in other databases such as Protein Identification Resources (2). N-TERMINAL shows the N-terminal sequence of five amino acids which may help to show the unambiguous numbering of th e sequence. CHANGE indicates the position and kind of mutations, such as amino acid substitution, insertion and deletion, denoted with a specific notation. Any functional or structural features (FUNCTION, STRUCTURE, STABILITY,etc) observed in the mutant are described immediately after ''CHANGE''. Relative differences in activity and/or stability, in comparison with the wild-type protein, are indicated with symbols (- -),(-),(=),(+) or (+ +). Complete loss of activity is denoted as (0). Data Submission A data submission system was newly prepared in the PMD. We welcome the authors of articles published in academic journals to submit their own mutant data to the PMD. After checking the contents, we will register the data with a unique accession number.

Proper citation: Protein Mutant Database (RRID:SCR_007878) Copy   

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http://rebase.neb.com/rebase/

Database of information about restriction enzymes and related proteins containing published and unpublished references, recognition and cleavage sites, isoschizomers, commercial availability, methylation sensitivity, crystal, genome, and sequence data. DNA methyltransferases, homing endonucleases, nicking enzymes, specificity subunits and control proteins are also included. Several tools are available including REBsites, BLAST against REBASE, NEBcutter and REBpredictor. Putative DNA methyltransferases and restriction enzymes, as predicted from analysis of genomic sequences, are also listed. REBASE is updated daily and is constantly expanding. Users may submit new enzyme and/or sequence information, recommend references, or send them corrections to existing data. The contents of REBASE may be browsed from the web and selected compilations can be downloaded by ftp (ftp.neb.com). Additionally, monthly updates can be requested via email.,

Proper citation: REBASE (RRID:SCR_007886) Copy   

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http://www.mouseatlas.org/

A portal to the Mouse Atlas of Gene Expression Project and Dissecting Gene Expression Networks in Mammalian Organogenesis Project. This Atlas will define the normal state for many tissues by determining, in a comprehensive and quantitative fashion, the number and identity of genes expressed throughout development. The resource will be comprehensive, quantitative, and publicly accessible, containing data on essentially all genes expressed throughout select stages of mouse development. Serial Analysis of Gene Expression (SAGE) is the gene expression methodology of choice for this work. Unlike expressed sequence tags (ESTs) and gene chip data, SAGE data are independent of prior gene discovery and are quantitative. Furthermore, SAGE data are digital, easily exchanged between laboratories for comparison and can be added to by scientists for years to come. Thus, this Atlas will include a data structure and data curation strategy that will facilitate the ongoing collection of gene expression data, even after the completion of this project. The Mouse Atlas project compromises 202 SAGE Libraries from 198 tissues. The list of libraries is available in a number of different groupings, including groups of libraries taken from specific tissue locations and libraries taken from specific developmental stages. Furthermore, this atlas will assemble gene expression profiles for a few focused experiments that will test hypotheses related to the techniques employed, tumor models and models of abnormal development. This will test the resource and provide quality control, validation and demonstrate applicability. Additionally, The Mammalian Organogenesis - Regulation by Gene Expression Networks (MORGEN) project will provide a complete, permanent, and accurate picture of mouse gene expression in the heart (atrioventricular canal and outflow tract), pancreas, and liver; new techniques to understand the interplay of proteins governing the expression of genes key to the development of these organ systems; and the identification of the master regulatory switches that control development of the tissues.

Proper citation: Mouse Gene Expression at the BC Cancer Agency (RRID:SCR_008091) Copy   

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http://mitores.ba.itb.cnr.it

MitoRes, is a comprehensive and reliable resource for massive extraction of sequences and sub-sequences of nuclear genes and encoded products targeting mitochondria in metazoa. It has been developed for supporting high-throughput in-silico analyses aimed to studies of functional genomics related to mitochondrial biogenesis, metabolism and to their pathological dysfunctions. It integrates information from the most accredited world-wide databases to bring together gene, transcript and encoded protein sequences associated to annotations on species name and taxonomic classification, gene name, functional product, organelle localization, protein tissue specificity, Enzyme Classification (EC), Gene Ontology (GO) classification and links to other related public databases. The section Cluster, has been dedicated to the collection of data on protein clustering of the entire catalogue of MitoRes protein sequences based on all versus all global pair-wise alignments for assessing putative intra- and inter-species functional relationships. The current version of MitoRes is based on the UniProt release 4 and contains 64 different metazoan species. The incredible explosion of knowledge production in Biology in the past two decades has created a critical need for bioinformatic instruments able to manage data and facilitate their retrieval and analysis. Hundreds of biological databases have been produced and the integration of biological data from these different resources is very important when we want to focus our efforts towards the study of a particular layer of biological knowledge. MitoRes is a completely rebuilt edition of MitoNuc database, which has been extensively modified to deal successfully with the challenges of the post genomic era. Its goal is to represent a comprehensive and reliable resource supporting high-quality in-silico analyses aimed to the functional characterization of gene, transcript and amino acid sequences, encoded by the nuclear genome and involved in mitochondrial biogenesis, metabolism and pathological dysfunctions in metazoa. The central features of MitoRes are: # an integrated catalogue of protein, transcript and gene sequences and sub-sequences # a Web-based application composed of a wide spectrum of search/retrieval facilities # a sequence export manager allowing massive extraction of bio-sequences (genes, introns, exons, gene flanking regions, transcripts, UTRs, CDS, proteins and signal peptides) in FASTA, EMBL and GenBank formats. It is an interconnected knowledge management system based on a MySQL relational database, which ensures data consistency and integrity, and on a Web Graphical User Interface (GUI), built in Seagull PHP Framework, offering a wide range of search and sequence extraction facilities. The database is compiled extracting and integrating information from public resources and data generated by the MitoRes team. The MitoRes database consists of comprehensive sequence entries whose core data are protein, transcript and gene sequences and taxonomic information describing the biological source of the protein. Additional information include: bio-sequences structure and location, biological function of protein product and dynamic links to both, external public databases used as data resources and public databases reporting complementary information. The core entity of the MitoRes database is represented by the protein so that each MitoRes entry is generated for each protein reported in the UniProt database as a nuclear encoded protein involved in mitochondrial biogenesis and function. Sponsors: MitoRes has been supported by Ministero Universit e Ricerca Scientifica, Italy (PRIN, Programma Biotecnologie legge 95/95-MURST 5, Proiect MURST Cluster C03/2000, CEGBA). Currently it is supported by operating grants from the Ministero dellIstruzione, dellUniversit e della Ricerca (MIUR), Italy (PNR 2001-2003 (FIRB art.8) D.M. 199, Strategic Program: Post-genome, grant 31-063933 and Project n.2, Cluster C03 L. 488/929).

Proper citation: MitoRes (RRID:SCR_008208) Copy   

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http://medblast.sibsnet.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. An algorithm that finds articles most relevant to a genetic sequence. In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here, a new literature-mining tool MedBlast is developed, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided. The genome sequencing projects generate such a large amount of data every day that many molecular biologists often encounter some sequences that they know nothing about. Literature is usually the principal resource of such information. It is relatively easy to mine the articles cited by the sequence annotation; however, it is a difficult task to retrieve those relevant articles without direct citation relationship. The related articles are those described in the given sequence (gene/protein), or its redundant sequences, or the close homologs in various species. They can be divided into two classes: direct references, which include those either cited by the sequence annotation or citing the sequence in its text; indirect references, those which contain gene symbols of the given sequence. A few additional issues make the task even more complicated: (1) symbols may have aliases; and (2) one sequence may have a couple of relatives that we want to take into account too, which include redundant (e.g. protein and gene sequences) and close homologs. Here the issues are addressed by the development of the software MedBlast, which can retrieve the related articles of the given sequence automatically. MedBlast uses BLAST to extend homology relationships, precompiled species-specific thesauruses, a useful semantics technique in natural language processing (NLP), to extend alias relationship, and EUtilities toolset to search and retrieve corresponding articles of each sequence from PubMed. MedBlast take a sequence in FASTA format as input. The program first uses BLAST to search the GenBank nucleic acid and protein non-redundant (nr) databases, to extend to those homologous and corresponding nucleic acid and protein sequences. Users can input the BLAST results directly, but it is recommended to input the result of both protein and nucleic acid nr databases. The hits with low e-values are chosen as the relatives because the low similarity hits often do not contain specific information. Very long sequences, e.g. 100k, which are usually genomic sequences, are discarded too, for they do not contain specific direct references. User can adjust these parameters to meet their own needs.

Proper citation: MedBlast (RRID:SCR_008202) Copy   

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http://www.koki.hu/main.php?folderID=903

The aim of this laboratory is to understand how information is encoded in specific spatiotemporal activity patterns and structural configurations at the circuit, cellular, and molecular levels in the hippocampus, thereby enabling the process of memory. A major task is to find the neuronal codes of internal representations of memory items and the mapping rules between the levels of gene expression/proteins synthesis and the level of cognitive processing. Novel combinations of approaches, including multiple single-cell recording technology, patch-clamp electrophysiology, neuroanatomy/neurochemistry at the cellular and subcellular levels, and computational models are employed to test specific hypotheses about that mapping process (such as local circuit anatomy and activity-dependent short-term and long-term synaptic plasticity). Collaborations within the Institute allows the group to also incorporate gene targeting methods and behavioral learning/memory tests in their methodological repertoire. The laboratory has been focusing on the normal and pathological (epileptic, ischemic) activity of cortical networks, with particular attention to the generation of behaviour-dependent population discharge patterns (theta and gamma oscillations, hippocampal sharp waves). Anatomical, in vitro and in vivo electrophysiological, pharmacological and molecular techniques and modeling are combined to elucidate the functional roles of inhibitory cell types in the control of population synchrony and synaptic plasticity in the hippocampus, their local and subcortical modulation via selective afferent pathways (GABAergic and cholinergic septal, as well as serotonergic raphe input) and pre- or postsynaptic receptors. An expanding new direction of research is related to the role of endocannabinoid signaling in the activity-dependent modulation of GABAergic and glutamatergic transmission, and its involvement in anxiety-like behavior.

Proper citation: Institute of Experimental Medicine of the Hungarian Academy of Sciences: Laboratory of Cerebral Cortext Reserach (RRID:SCR_008041) Copy   

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