Bioinformatics Databases
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Bioinformatics databases aim to manage the complexity of life by integrating diverse biological data types. Relational databases use standardized identifiers and data formats to store sequence, expression, proteomic, and metabolomic data. Cross-referencing multiple databases through data warehousing and centralized schemas allows for functional querying of biological networks and neighborhoods. Future directions include greater use of machine learning, data mining, and global data standards.
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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
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PRIMARY DATABASE
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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
Bioinformatics principles and applications
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This document provides an overview of bioinformatics and bioinformatics databases. It defines bioinformatics as the application of information technology to molecular biology to analyze and interpret biological data. This includes tasks like mapping and analyzing DNA and protein sequences. The document discusses how bioinformatics databases are used to store and manage the large amounts of biological data generated. It describes the characteristics of biological databases and how they are used for querying and retrieving sequence information. Key areas of bioinformatics research and important sequence databases are also summarized.Primary and secondary database
INTRODUCTION
WHAT IS DATA AND DATABASE?
WHAT IS BIOLOGICAL DATABASE?
TYPES OF BIOLOGICAL DATABASE
PRIMARY DATABASE
Nucleic acid sequence database
Protein sequence database
SECONDARY DATABASE
COMPOSITE DATABASE
TERTIARY DATABASE
WHY NEED?
CONCLUSION
REFRENCES
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Data acquisition
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Principal Component Analysis
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This document discusses biological databases. It begins by defining what a database is and describing database architecture. It then discusses several major types of biological databases including nucleotide sequence databases like GenBank, protein sequence databases like PDB, and collaborative databases. Specific databases discussed in detail include GenBank, NCBI, DDBJ, Swiss-Prot, TrEMBL, and UniProt. The document explains the purpose and contributions of these different biological databases.
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This document discusses biological databases. It defines a biological database as a collection of structured, searchable, and periodically updated biological data like protein sequences, molecular structures, and DNA sequences. It notes that biological data is heterogeneous, high-volume, uncertain, dynamically changing, and integrated from various global sources. The key functions of biological databases are to make biological data available worldwide in a computer-readable format. They are broadly classified into sequence, structure, and pathway databases. Some examples of important biological databases discussed are Swiss-Prot, PDB, GenBank, and COGs.
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Biological database
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LECTURE NOTES ON BIOINFORMATICS
introduction,history scope and applications of
relation to other fields , bioinformatics,biological databases,computers internet,sequence development, and
introduction to sequence development and alignment
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The EMBL Australian Bioinformatics Resource (EMBL-ABR) is a distributed national research infrastructure that provides bioinformatics support to life science researchers in Australia. It has a hub-and-nodes structure with the hub hosted at the Victorian Life Science Computation Initiative at the University of Melbourne and 10 nodes located across Australian institutions. EMBL-ABR aims to increase Australia's capacity for bioinformatics research and data science, provide training in bioinformatics, and enable participation in international collaborations.
FAIRy Stories
Findable Accessable Interoperable Reusable < data |models | SOPs | samples | articles| * >. FAIR is a mantra; a meme; a myth; a mystery; a moan. For the past 15 years I have been working on FAIR in a bunch of projects and initiatives in Life Science projects. Some are top-down like Life Science European Research Infrastructures ELIXIR and ISBE, and some are bottom-up, supporting research projects in Systems and Synthetic Biology (FAIRDOM), Biodiversity (BioVel), and Pharmacology (open PHACTS), for example. Some have become movements, like Bioschemas, the Common Workflow Language and Research Objects. Others focus on cross-cutting approaches in reproducibility, computational workflows, metadata representation and scholarly sharing & publication. In this talk I will relate a series of FAIRy tales. Some of them are Grimm. Some have happy endings. Who are the villains and who are the heroes? What are the morals we can draw from these stories?
Research data and scholarly publications: going from casual acquaintances to ...
Presented to ALPSP annual meeting 2011 in Oxfordshire UK during a session entitled "Abort Retry Fail? Data and the scholarly literature"
Research Objects: more than the sum of the parts
Workshop on Managing Digital Research Objects in an Expanding Science Ecosystem, 15 Nov 2017, Bethesda, USA
https://www.rd-alliance.org/managing-digital-research-objects-expanding-science-ecosystem
Research output is more than just the rhetorical narrative. The experimental methods, computational codes, data, algorithms, workflows, Standard Operating Procedures, samples and so on are the objects of research that enable reuse and reproduction of scientific experiments, and they too need to be examined and exchanged as research knowledge.
A first step is to think of Digital Research Objects as a broadening out to embrace these artefacts or assets of research. The next is to recognise that investigations use multiple, interlinked, evolving artefacts. Multiple datasets and multiple models support a study; each model is associated with datasets for construction, validation and prediction; an analytic pipeline has multiple codes and may be made up of nested sub-pipelines, and so on. Research Objects (http://researchobject.org/) is a framework by which the many, nested and contributed components of research can be packaged together in a systematic way, and their context, provenance and relationships richly described.
Big Data Repository for Structural Biology: Challenges and Opportunities by P...
SBGrid (Morin et al., 2013, eLIFE and www.sbgrid.org) is a Harvard based structural biology global computing consortium with a primary focus on the curation of research software. Dr. Sliz will discuss a recent SBGrid project that aims to establish a repository for experimental datasets from SBGrid laboratories. Issues of handling large data volumes, data validation and repository sustainability will be addressed in this talk.
Knowledge Exchange, Nov 2011, Bonn
Keynote presented to KE workshop held in conjunction with the release of the report "A Surfboard for Riding the Wave
Towards a four country action programme on research data": http://www.knowledge-exchange.info/Default.aspx?ID=469
Data Infrastructure for Coastal and Estuarine Science
This talk was given at the Atlantic Estuarine Research Society at their 2014 Sprint meeting in Ocean City, Maryland, USA
Enriching Scholarship 2014 Beyond the Journal Article: Publishing and Citing ...
The document discusses data sharing policies and mandates from various organizations including federal funding agencies in the US and internationally, journals, and a paradigm shift toward more transparent and collaborative research that integrates publications and data. Key points include requirements for data management plans from NIH and NSF, expectations of funding agencies in other countries to maximize access to research data, a journal policy requiring data to be made available, and challenges around measuring the impact of shared data given the lack of common practices and standards for citing data.
VIVO: enabling the discovery of research and scholarship
An introduction to VIVO, an open source, semantic web application that enables discovery of research and scholarship across institutions and one library's role in its implementation and development.
Curation and Preservation of Crystallography Data
A presentation given by Manjula Patel (UKOLN) at "Chemistry in the Digital Age: A Workshop connecting research and education", June 11-12th 2009, Penn State University,
http://www.chem.psu.edu/cyberworkshop09
CTSA Inventory Resource Web Presence
The document describes the CTSA Inventory Resource Web Presence (CIRWP), a web-accessible and searchable inventory of research resources across the CTSA consortium. It outlines the development of CIRWP, including building an informatics infrastructure based on standards, extending ontologies to annotate resource descriptions, and deploying web services and tools to enable a distributed inventory. CIRWP includes full or partial inventories from 37 CTSA sites cataloging over 370 informatics resources. The document discusses future goals of CIRWP such as accelerating harmonization across organizations and outreach, and highlights evaluations conducted to design CIRWP with user-centered approaches.
Being FAIR: Enabling Reproducible Data Science
Talk presented at Early Detection of Cancer Conference, OHSU, Portland, Oregon USA, 2-4 Oct 2018, http://earlydetectionresearch.com/ in the Data Science session
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ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
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みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
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Bioinformatics Databases
- 1. BIOINFORMATICS DATABASES: MANAGING THE COMPLEXITY OF LIFE Christopher Schlosberg CS 411 Graduate Project
- 3. Protein Sequence Search [12]
- 5. General Bio-DB Development Considerations [11] [2]
- 8. SQL Implementation for Feeder DBs [9]