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This document describes the composition and research interests of the Grupo de Bioinformática & EvoluciÃ3n Molecular. The group consists of 5 PhDs, 3 postdocs, 1 IPP, and 1 TU, with members from Spain, Portugal, Brazil, Venezuela, Peru and Romania specializing in fields including biology, mathematics, computer science and chemistry. Their research lines focus on topics such as the computational prediction of the genetic code, molecular evolution, phylogenomics, bacterial genomics and software development, and their bioinformatic needs include high performance computing, web services development, machine learning and computational statistics.
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Biological database by kk sahu
INTRODUCTION
HISTORY
WHAT ARE THE DATABASE…?
WHY DATABASE….?
THE “PERFECT” DATABASE
IDENTIFIERS and ACCESSION NUMBER
TECHNICAL DESIGN
MAINTAINANCE OF BIOLOGICAL DATABASES..
GENERAL FEATURES
SOURCES OF BIOLOGICAL DATA…
DIFFERENT TYPES OF BIOLOGICAL DATABASE
FUNCTION
DATA ENTRY AND QUALITY CONTROL
AVAILIBILITY
APPLICATION
DATA RECORD AT THE YEAR 2004
CONCLUSION
REFFERENCES
Biological databases
This document summarizes different types of biological data and biological databases. It discusses primary databases like GenBank, EMBL and DDBJ that contain raw nucleotide sequence data. Secondary databases like KEGG and Pfam analyze and annotate primary database content. Composite databases like NCBI aggregate data from multiple primary sources. Protein databases discussed include Swiss-Prot, TrEMBL, PDB, and Pfam. Structural databases such as SCOP, CATH and PDB organize protein structures.
Bioinformatics in a Nutshell
This document discusses bioinformatics and biology at various levels of organization. It begins by explaining that biology is extremely complex due to the hierarchical organization of life, from molecules to ecosystems. It then provides definitions of bioinformatics from Wikipedia and other sources, emphasizing that it is an interdisciplinary field that uses computer science and other approaches to study vast amounts of biological data. Examples of different types of biological data and areas of bioinformatics research are given, such as sequence analysis, databases, and structural bioinformatics. Overall, the document provides a high-level introduction to bioinformatics and its role in understanding biology.
Biological databases
In the era of computers life sciences databases are still understated. Here is my presentation on biological databases. Complete classification of different databases.
For more presentations and work come and visit
https://www.linkedin.com/in/shradheya-r-r-gupta-54492984/
Databases ii
The document discusses various types of biological databases including sequence databases, structure databases, genome databases, and model organism databases. It provides examples of nucleotide databases like Genbank, DDBJ, EMBL-EBI, and TIGR. Genome browsers like UCSC Genome Browser, Ensembl browser, and Integrated Genome Browser are also mentioned. Other topics covered include the Encyclopedia of Life, India Biodiversity, Barcode of Life, data retrieval schemes, bibliographic databases, and database journals.
RML NCBI Resources
NCBI has developed a powerful suite of online biomedical and bioinformatics resources, including old friends like PubMed and OMIM and newer resources such as Genome. This collection of databases and tools are widely used by scientists and medical professionals across the world. With such a wealth of information, it is easy to get overwhelmed. Join us for an overview to NCBI resources for the information professional with an emphasis on biodata connectivity. No science degree required!
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Recommended
Biological database by kk sahu
INTRODUCTION
HISTORY
WHAT ARE THE DATABASE…?
WHY DATABASE….?
THE “PERFECT” DATABASE
IDENTIFIERS and ACCESSION NUMBER
TECHNICAL DESIGN
MAINTAINANCE OF BIOLOGICAL DATABASES..
GENERAL FEATURES
SOURCES OF BIOLOGICAL DATA…
DIFFERENT TYPES OF BIOLOGICAL DATABASE
FUNCTION
DATA ENTRY AND QUALITY CONTROL
AVAILIBILITY
APPLICATION
DATA RECORD AT THE YEAR 2004
CONCLUSION
REFFERENCES
Biological databases
This document summarizes different types of biological data and biological databases. It discusses primary databases like GenBank, EMBL and DDBJ that contain raw nucleotide sequence data. Secondary databases like KEGG and Pfam analyze and annotate primary database content. Composite databases like NCBI aggregate data from multiple primary sources. Protein databases discussed include Swiss-Prot, TrEMBL, PDB, and Pfam. Structural databases such as SCOP, CATH and PDB organize protein structures.
Bioinformatics in a Nutshell
This document discusses bioinformatics and biology at various levels of organization. It begins by explaining that biology is extremely complex due to the hierarchical organization of life, from molecules to ecosystems. It then provides definitions of bioinformatics from Wikipedia and other sources, emphasizing that it is an interdisciplinary field that uses computer science and other approaches to study vast amounts of biological data. Examples of different types of biological data and areas of bioinformatics research are given, such as sequence analysis, databases, and structural bioinformatics. Overall, the document provides a high-level introduction to bioinformatics and its role in understanding biology.
Biological databases
In the era of computers life sciences databases are still understated. Here is my presentation on biological databases. Complete classification of different databases.
For more presentations and work come and visit
https://www.linkedin.com/in/shradheya-r-r-gupta-54492984/
Databases ii
The document discusses various types of biological databases including sequence databases, structure databases, genome databases, and model organism databases. It provides examples of nucleotide databases like Genbank, DDBJ, EMBL-EBI, and TIGR. Genome browsers like UCSC Genome Browser, Ensembl browser, and Integrated Genome Browser are also mentioned. Other topics covered include the Encyclopedia of Life, India Biodiversity, Barcode of Life, data retrieval schemes, bibliographic databases, and database journals.
RML NCBI Resources
NCBI has developed a powerful suite of online biomedical and bioinformatics resources, including old friends like PubMed and OMIM and newer resources such as Genome. This collection of databases and tools are widely used by scientists and medical professionals across the world. With such a wealth of information, it is easy to get overwhelmed. Join us for an overview to NCBI resources for the information professional with an emphasis on biodata connectivity. No science degree required!
Joe Betts-LaCroix at Health Extension Salon #1
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NCBI Boot Camp for Beginners Slides
The NCBI Boot Camp for Beginners was designed to offer an overview of the NCBI suite of resources. In the first half of the presentation, highlighted databases were covered in four main categories: literature, sequences, genes & genomes and expression & structure. The second half of the class used the apolipoprotein A as a query that was explored through many of the NCBI databases, from identifying the reference sequences to a structural analysis of the Cys130Arg variant.
Major biological nucleotide databases
This document discusses major biological databases. It describes three types of biological databases: primary databases that contain original experimental data, secondary databases that contain additional derived information from primary databases, and composite databases that combine data from multiple sources. The document focuses on describing GenBank, a primary sequence database maintained by the National Center for Biotechnology Information. It provides details on how sequences are submitted to GenBank and how entries are formatted, including information contained in various fields like LOCUS, DEFINITION, and FEATURES. The document also briefly introduces the European Molecular Biology Laboratory database, EMBL, which collaborates with GenBank and DDBJ to exchange nucleotide sequence data daily.
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This document provides information about several nucleotide and protein sequence databases including:
- INSDC (International Nucleotide Sequence Database Collaboration) which includes GenBank, EMBL, and DDBJ.
- GenBank which contains over 80 billion nucleotide bases from 76 million sequences and doubles in size every 18 months. The top species represented are human, mouse, rat, cattle, and maize.
- EMBL and DDBJ which are similar to GenBank in content and format but maintained by different collaborations. Secondary databases like UniProt, PROSITE and PRINTS/BLOCKS provide additional annotation and analysis of sequences.
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Biological databases provide various types of molecular biology data including sequences, structures, and functional information. Sequence databases like GenBank provide nucleotide sequences while UniProt provides protein sequences. Structure databases like PDB provide 3D protein structures. These databases contain sequences, annotations, references, and tools for analysis. They are periodically updated and cross-referenced for comprehensive molecular data.
Tools and database of NCBI
The document discusses the National Center for Biotechnology Information (NCBI). It provides background that NCBI is part of the National Library of Medicine and houses databases relevant to biotechnology and biomedicine. It describes some of NCBI's major databases, including GenBank for DNA sequences and PubMed for biomedical literature. The document also discusses the BLAST tool and provides examples of some of NCBI's databases, such as the Nucleotide, Protein, and Structural databases.
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Ensembl genome
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100505 koenig biological_databases
This document summarizes biological databases and provides examples. It discusses:
1. The need for biological databases to store and analyze the large amounts of data generated by experiments.
2. Examples of common database types including nucleotide sequences, protein sequences, enzymes, pathways, literature, and more.
3. How sequence alignment tools like BLAST are used to compare queries to database entries and identify similar sequences.
New insights into the human genome by ENCODE project
The ENCODE project aims to map all functional elements in the human genome. It has identified protein-coding genes covering 2.94% of the genome. ENCODE has also mapped regions of transcription, RNA transcription start sites, protein-bound regions including those bound by 119 DNA-binding proteins, DNase I hypersensitive sites, and regions of histone modification and DNA methylation across different cell types. While providing new insights, the project is still far from complete in mapping the full spectrum of functional elements in the human genome.
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Jack Ryan Reifert is seeking a post-doctoral position in molecular mechanisms of age-related human diseases. He received his Ph.D. in Molecular, Cellular, and Developmental Biology from UCSB, where his dissertation research investigated amyloid beta-induced neurodegeneration and the role of tau phosphorylation and cleavage. He has research experience in academia and industry, including publications, and is currently investigating tau fragmentation and amyloid beta signaling in neurodegeneration.
Human genome project
The document summarizes the Human Genome Project (HGP), which had the goals of identifying all human genes, determining the sequences of DNA base pairs that make up human DNA, storing this information in databases, and addressing ethical issues. Key milestones included completing a working draft in 2000 and fully sequencing the genome in 2003, two years ahead of schedule. The HGP and a private company collaborated to obtain the DNA sequence.
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BLAST; Introduction, Homepage and types of BLAST
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References
Acknowledgements
NCBI
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UMIC core: umic.info
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Upcoming webinars schedule: https://dknet.org/about/webinar
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This document discusses major biological databases. It describes three types of biological databases: primary databases that contain original experimental data, secondary databases that contain additional derived information from primary databases, and composite databases that combine data from multiple sources. The document focuses on describing GenBank, a primary sequence database maintained by the National Center for Biotechnology Information. It provides details on how sequences are submitted to GenBank and how entries are formatted, including information contained in various fields like LOCUS, DEFINITION, and FEATURES. The document also briefly introduces the European Molecular Biology Laboratory database, EMBL, which collaborates with GenBank and DDBJ to exchange nucleotide sequence data daily.
Beiko taconic-nov3
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Biological databases
This document provides information about several nucleotide and protein sequence databases including:
- INSDC (International Nucleotide Sequence Database Collaboration) which includes GenBank, EMBL, and DDBJ.
- GenBank which contains over 80 billion nucleotide bases from 76 million sequences and doubles in size every 18 months. The top species represented are human, mouse, rat, cattle, and maize.
- EMBL and DDBJ which are similar to GenBank in content and format but maintained by different collaborations. Secondary databases like UniProt, PROSITE and PRINTS/BLOCKS provide additional annotation and analysis of sequences.
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Bioinformatic databases 2
Biological databases provide various types of molecular biology data including sequences, structures, and functional information. Sequence databases like GenBank provide nucleotide sequences while UniProt provides protein sequences. Structure databases like PDB provide 3D protein structures. These databases contain sequences, annotations, references, and tools for analysis. They are periodically updated and cross-referenced for comprehensive molecular data.
Tools and database of NCBI
The document discusses the National Center for Biotechnology Information (NCBI). It provides background that NCBI is part of the National Library of Medicine and houses databases relevant to biotechnology and biomedicine. It describes some of NCBI's major databases, including GenBank for DNA sequences and PubMed for biomedical literature. The document also discusses the BLAST tool and provides examples of some of NCBI's databases, such as the Nucleotide, Protein, and Structural databases.
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The document provides an overview of several agricultural databases and genome research programs. It discusses the National Center for Biotechnology Information (NCBI) and databases it maintains, including GenBank, PubMed, PubChem, dbSNP, and others. It also describes other plant-focused databases like Gramene, GrainGenes, PlantGDB, TIGR, UK CropNet, and databases for specific crops like MaizeDB, TAIR, Rice Genome Research Program, and the US Wheat Genome Project. Genome assembly and analysis software is also briefly mentioned.
Ensembl genome
Ensembl Genomes is a portal that provides integrated access to genome-scale data for non-vertebrate species. It was developed using the Ensembl genome annotation and visualization platform. It consists of sub-portals for bacteria, protists, fungi, plants and invertebrate metazoa that complement the vertebrate genomes available in Ensembl. It provides graphical views of genomes and genes using the Ensembl genome browser software. Data is retrieved through interfaces like BioMart and APIs that access relational databases describing genomic features, sequences and identifiers. Tools like the Assembly Converter and Variant Effect Predictor are also available.
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This document provides information about databases in molecular biology. It defines what a database is, including that it is a structured collection of data held in computer storage that incorporates software to make it accessible. It notes some examples of biological databases, categories of databases for life sciences, and some large database resources like NCBI, EBI, and DDBJ. It also discusses literature databases and alerting services. Finally, it provides details on Boolean syntax used for searching databases.
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This document summarizes biological databases and provides examples. It discusses:
1. The need for biological databases to store and analyze the large amounts of data generated by experiments.
2. Examples of common database types including nucleotide sequences, protein sequences, enzymes, pathways, literature, and more.
3. How sequence alignment tools like BLAST are used to compare queries to database entries and identify similar sequences.
New insights into the human genome by ENCODE project
The ENCODE project aims to map all functional elements in the human genome. It has identified protein-coding genes covering 2.94% of the genome. ENCODE has also mapped regions of transcription, RNA transcription start sites, protein-bound regions including those bound by 119 DNA-binding proteins, DNase I hypersensitive sites, and regions of histone modification and DNA methylation across different cell types. While providing new insights, the project is still far from complete in mapping the full spectrum of functional elements in the human genome.
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The document summarizes the Human Genome Project (HGP), which had the goals of identifying all human genes, determining the sequences of DNA base pairs that make up human DNA, storing this information in databases, and addressing ethical issues. Key milestones included completing a working draft in 2000 and fully sequencing the genome in 2003, two years ahead of schedule. The HGP and a private company collaborated to obtain the DNA sequence.
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The National Center for Biotechnology Information (NCBI) was created in 1988 as part of the National Library of Medicine at NIH. It establishes public databases for biological research, develops software tools for sequence analysis, and disseminates biomedical information from its location in Bethesda, MD. NCBI houses several integrated databases including PubMed, GenBank, RefSeq, and UniGene that contain literature, sequences, gene information, and more.
Transcription in eucriotes,_procariotes_and_rna_processing 2
This document discusses two scientific articles about recent advances in the fields of RNA processing and nanotechnology. The first article identifies that accumulation of Alu RNA in the retina causes macular degeneration due to decreased levels of the "dicer" enzyme, and proposes increasing dicer or blocking Alu RNA as potential treatments. The second article finds that modifying RNA's sugar ring prevents degradation by RNAse enzymes, making RNA more stable for use in nanotechnology such as cancer treatments. Both discoveries could help develop prevention strategies for diseases like macular degeneration and cancer.
Bioinf2Bio Oportunidades
Sessão de Apresentação do Mestrado em Bioinformática e Biologia Computacional, dia 6 de Maio de 2014 às 16h30 no Anfiteatro da FFCUL
Institute of Learning in Retirement - Miami University (Ohio)
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This document summarizes Professor M. Dominik Fischer's presentation on gene therapy and genome editing for retinitis pigmentosa. It provides background on retinitis pigmentosa and how it affects approximately 200,000 people in the EU. It discusses current gene therapy clinical trials targeting conditions like choroideremia and retinitis pigmentosa. It also outlines the concept of CRISPR/Cas gene editing and challenges with applying it to retinal tissue, as well as potential future applications of gene therapy and editing to treat additional forms of inherited retinal diseases.
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UMIC core: umic.info
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The document provides information about a short course on next generation sequencing and analysis of sequence variants. It includes an agenda with sessions on introduction to NGS applications in medical research, data analysis pipelines, interpretation of variants, and tools for predicting pathogenicity. It also provides background on the organizing institutions, the CNAG sequencing center and its projects, and an overview of bioinformatics analysis pipelines and resources.
Math, Stats and CS in Public Health and Medical Research
Jessica Minnier gave a talk on her career path from studying mathematics at Lewis & Clark College to her current position as an Assistant Professor in biostatistics. She discussed how biostatistics, bioinformatics, and computational biology are applied in medical research, using examples like analyzing RNA sequencing data and building predictive models from electronic health records. Minnier also shared resources for learning more about careers in public health research and statistics.
Bioinformatics seminar
Brief idea on Genomics,Transcriptomics,Metabolomics and Proteomics.
overview on Biological databases and its types.
bioinfomatics
Bioinformatics is an interdisciplinary field that uses computational tools to analyze and manage biological data such as genes, genomes, proteins, and medical information. It involves developing mathematical models to understand relationships in complex biological systems. Key areas include analyzing protein and gene sequences, structures, and functions; understanding evolution and molecular interactions; and developing "virtual cells" through integrated modeling. Major challenges include integrating heterogeneous biological data sources and developing robust computational methods.
DNA based Techniques - PCR BASIC CONCEPTS.pptx
This document provides information about PCR (polymerase chain reaction), including:
1) PCR can be used to amplify specific DNA sequences from complex genomes by billions of copies in a few hours, solving issues of specificity and amplification.
2) Kary Mullis invented PCR in 1983 and it has many uses including forensics, disease diagnosis, archaeology, and basic research.
3) The PCR reaction requires template DNA, primers, nucleotides, DNA polymerase, magnesium ions, buffer, and water. During cycles of heating and cooling, the DNA is denatured, primers anneal, and the polymerase synthesizes new DNA strands.
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Xb5
- 1. Grupo de Bioinformática & Evolución Molecular darwin.uvigo.es
- 2. Composition • 5 PhD • 3 postdocs • 1 IPP • 1 TU • 7 biologists, 1 mathematician, 1 informatic engineer, 1 chemist. • Spain, Portugal, Brazil, Venezuela, Peru, Romenia.
- 3. Members (I) • Graciela Sotelo (PhD; biologist): crustacean phylogeography. • Miguel Arenas (PhD; chemist): recombination and HIV evolution. • Mateus Patricio (PhD; computer science): genetic code prediction. • Sara Rocha (PhD; biologist): reptile biogeography. • Miguel Fonseca (PhD; biologist): mtDNA evolution.
- 4. Members (II) • Alpar Vajk-Kramer (postdoc; mathematician): numerical optimization. • Leo Arbiza (postdoc; biologist): computational genomics. • Leo Martins (postdoc; biologist): Bayesian phylogenomics. • Carlos Canchaya (IPP; biologist): comparative genomics. • David Posada (TU; biologist): models of molecular evolution, detection of recombination
- 5. Research lines in bioinformatics • Computational prediction of the genetic code. • Molecular evolution, genome structure and gene function. • Phylogenomics and models of genome evolution. • Bacterial and phage comparative genomics • Software development.
- 6. Bioinformatic needs • HPC: parallelization, multi-core environments, GPU. • Development of web services. • Classification and machine learning. • Computational statistics: numerical optimization,likelihod, Bayesian, MCMC.