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PubMed is an interface for searching biomedical and life sciences journal articles developed by the National Center for Biotechnology Information at the US National Library of Medicine. It provides bibliographic details and abstracts of published articles free of cost. Medical subject headings (MeSH) are used to index articles in a hierarchical vocabulary to provide consistency. Searches can be performed on the PubMed website using keywords or advanced search options to retrieve relevant records, though it does not provide full text articles. Additional tools help refine searches. While making content freely available, PubMed preserves copyright and represents documents in XML for long-term preservation of scientific literature. However, it does not support citation searching.
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Pub med
PubMed is a free database of over 23 million citations and abstracts for biomedical literature from Medline, life sciences journals, and online books. It is maintained by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM). PubMed provides bibliographic information and links to full-text content from publishers and libraries. Users can search PubMed using keywords, controlled vocabularies like MeSH, or advanced search techniques and filters to find relevant journal articles and resources.
Pub Med
This document provides an overview of the PubMed database. PubMed is an online database developed by the National Center for Biotechnology Information that allows users to access MEDLINE, a database of biomedical literature. The document discusses PubMed's history, coverage of over 19 million citations back to the 1950s, features like advanced search capabilities and links to full texts, and tutorials for searching and using PubMed.
Pubmed Basics
This document provides an overview of searching PubMed, including:
I. PubMed searches the MEDLINE database and provides access to over 21 million records and abstracts indexed with Medical Subject Headings (MeSH).
II. MeSH terms standardize topics across articles and help retrieve related articles that use different terminology for the same concept.
III. Searching PubMed involves using keywords that are matched to MeSH terms, and filters can then focus results; searching for a term as a "MeSH Major Topic" limits to articles where it is a primary topic.
IV. Full text of articles can be accessed through setting preferences in a NCBI account, using the UST OneSearch database which includes Pub
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This document provides an introduction to databases used for biological data. It defines key terms like data, information, and databases. It describes different types of biological databases including primary databases that contain original experimental data, and secondary databases that contain derived or analyzed data. Examples of primary databases include GenBank, EMBL, and PDB, while secondary databases include PROSITE, PRINTS, and Pfam that contain conserved protein motifs and families. The document also compares primary and secondary databases.
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The document provides an introduction to BLAST (Basic Local Alignment Search Tool), which is an algorithm used to compare gene and protein sequences to those in public databases. It discusses the types of BLAST programs, the BLAST algorithm, input/output, how to perform a BLAST search, and the functions and objectives of BLAST. Specifically, BLAST is faster than previous sequence comparison methods, it outputs alignments and statistical values to evaluate matches, and its main objectives are to identify related sequences and locate domains through local alignments.
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Pub med
PubMed is a free database of over 23 million citations and abstracts for biomedical literature from Medline, life sciences journals, and online books. It is maintained by the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM). PubMed provides bibliographic information and links to full-text content from publishers and libraries. Users can search PubMed using keywords, controlled vocabularies like MeSH, or advanced search techniques and filters to find relevant journal articles and resources.
Pub Med
This document provides an overview of the PubMed database. PubMed is an online database developed by the National Center for Biotechnology Information that allows users to access MEDLINE, a database of biomedical literature. The document discusses PubMed's history, coverage of over 19 million citations back to the 1950s, features like advanced search capabilities and links to full texts, and tutorials for searching and using PubMed.
Pubmed Basics
This document provides an overview of searching PubMed, including:
I. PubMed searches the MEDLINE database and provides access to over 21 million records and abstracts indexed with Medical Subject Headings (MeSH).
II. MeSH terms standardize topics across articles and help retrieve related articles that use different terminology for the same concept.
III. Searching PubMed involves using keywords that are matched to MeSH terms, and filters can then focus results; searching for a term as a "MeSH Major Topic" limits to articles where it is a primary topic.
IV. Full text of articles can be accessed through setting preferences in a NCBI account, using the UST OneSearch database which includes Pub
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The DNA Data Bank of Japan (DDBJ) is a biological database that collects DNA sequences. It is located at the National Institute of Genetics (NIG) in the Shizuoka prefecture of Japan. It is also a member of the International Nucleotide Sequence Database Collaboration or INSDC.
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This document provides an introduction to databases used for biological data. It defines key terms like data, information, and databases. It describes different types of biological databases including primary databases that contain original experimental data, and secondary databases that contain derived or analyzed data. Examples of primary databases include GenBank, EMBL, and PDB, while secondary databases include PROSITE, PRINTS, and Pfam that contain conserved protein motifs and families. The document also compares primary and secondary databases.
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The document provides an introduction to BLAST (Basic Local Alignment Search Tool), which is an algorithm used to compare gene and protein sequences to those in public databases. It discusses the types of BLAST programs, the BLAST algorithm, input/output, how to perform a BLAST search, and the functions and objectives of BLAST. Specifically, BLAST is faster than previous sequence comparison methods, it outputs alignments and statistical values to evaluate matches, and its main objectives are to identify related sequences and locate domains through local alignments.
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This presentation will tells about the Introduction and working of NCBI database and is informative for the beginners.
Ncbi
The National Center for Biotechnology Information (NCBI) was established in 1988 as part of the National Library of Medicine. NCBI houses numerous biomedical databases including those related to genes, proteins, molecular structures, gene expression, and biomedical literature. Users can utilize various tools on the NCBI site to search databases, perform sequence alignments using BLAST, and submit new sequences. Some key databases include GenBank (nucleotide sequences), PubMed (biomedical literature), and RefSeq (non-redundant reference sequences).
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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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.
Entrez databases
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blast bioinformatics
1. BLAST is a program that uses computer algorithms to compare a query DNA or protein sequence to sequence databases and identify sequences that resemble the query sequence above a certain threshold.
2. BLAST works by searching for short, exact matches between the query and database sequences, then extends the matches to find similar though not exact alignments.
3. Analyzing the BLAST results can provide information about the evolutionary relationship between the query sequence and matched sequences, such as whether they come from the same gene or protein family.
EMBL
The European Molecular Biology Laboratory (EMBL) is a molecular biology research institution supported by 22 member states. EMBL was created in 1974 and operates from five sites, performing basic research in molecular biology and molecular medicine. A key function of EMBL is the EMBL Nucleotide Sequence Database, maintained at the European Bioinformatics Institute, which incorporates and distributes nucleotide sequences from public sources as part of an international collaboration.
BLAST
Dr Avril Coghlan discusses the BLAST algorithm for comparing biological sequences and searching databases of DNA and protein sequences. BLAST is a fast heuristic method for sequence alignment and database searching. It works by first finding short words that are common between the query sequence and database sequences, and then extending the alignment around these words. BLAST is able to quickly search very large databases and find significant matches by calculating E-values, which estimate the statistical significance of matches. BLAST allows researchers to determine if a new sequence is similar to any known sequences and predict potential functions.
TrEMBL
TrEMBL is a computer-annotated protein sequence database created by Rolf Apweiler that contains translations of coding sequences from nucleotide databases like EMBL and GenBank as well as protein sequences from literature or submitted directly. The database provides automated classification and annotation to enrich the protein sequences.
Database in bioinformatics
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Introduction OF BIOLOGICAL DATABASE
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NCBI National Center for Biotechnology Information
NCBI National Center for Biotechnology InformationThapar Institute of Engineering & Technology, Patiala, Punjab, India
The National Center for Biotechnology Information advances science and health by providing access to biomedical and genomic informationBLAST
This document discusses the Basic Local Alignment Search Tool (BLAST), which allows users to compare a query DNA or protein sequence against sequence databases to find regions of local similarity. BLAST breaks the query into short words that are then searched for in database sequences. When words are found in common, BLAST extends the alignment in both directions to find higher-scoring matches. BLAST outputs include a graphical display of alignments, a hit list ranking matches by similarity score, and detailed alignments. BLAST has many applications, such as identifying species, establishing evolutionary relationships, DNA mapping, and locating protein domains.
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The Protein Data Bank (PDB) is a single worldwide database that stores 3D structural data of proteins and nucleic acids. It is operated by Rutgers University, the San Diego Supercomputer Center, and the Research Collaboratory for Structural Bioinformatics. The PDB is freely accessible online and contains over 76,000 biomolecular structure entries as of 2011. It uses a common file format to represent structural data and is updated weekly as new entries are submitted by researchers.
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PubMed provides links to the integrated molecular biology databases maintained by NCBI. These databases contain: DNA and protein sequences, genome mapping data, and 3‑D protein structures, aligned sequences from populations, and the Online Mendelian Inheritance in Man (OMIM). Links between MEDLINE records and sequence records make it easy to find MEDLINE abstracts associated with sequence records and vice versa.
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Ncbi
The National Center for Biotechnology Information (NCBI) was established in 1988 as part of the National Library of Medicine. NCBI houses numerous biomedical databases including those related to genes, proteins, molecular structures, gene expression, and biomedical literature. Users can utilize various tools on the NCBI site to search databases, perform sequence alignments using BLAST, and submit new sequences. Some key databases include GenBank (nucleotide sequences), PubMed (biomedical literature), and RefSeq (non-redundant reference sequences).
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
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.
Entrez databases
The document discusses biological databases and retrieval systems. It provides an overview of Entrez, a retrieval system developed by NCBI that allows integrated searches across multiple biological databases. It also describes how Entrez links related data between databases, and some key features of Entrez like limits, preview/index, and history. Additionally, it summarizes specific NCBI databases accessible through Entrez like PubMed and OMIM, as well as another retrieval system called SRS maintained by EBI.
blast bioinformatics
1. BLAST is a program that uses computer algorithms to compare a query DNA or protein sequence to sequence databases and identify sequences that resemble the query sequence above a certain threshold.
2. BLAST works by searching for short, exact matches between the query and database sequences, then extends the matches to find similar though not exact alignments.
3. Analyzing the BLAST results can provide information about the evolutionary relationship between the query sequence and matched sequences, such as whether they come from the same gene or protein family.
EMBL
The European Molecular Biology Laboratory (EMBL) is a molecular biology research institution supported by 22 member states. EMBL was created in 1974 and operates from five sites, performing basic research in molecular biology and molecular medicine. A key function of EMBL is the EMBL Nucleotide Sequence Database, maintained at the European Bioinformatics Institute, which incorporates and distributes nucleotide sequences from public sources as part of an international collaboration.
BLAST
Dr Avril Coghlan discusses the BLAST algorithm for comparing biological sequences and searching databases of DNA and protein sequences. BLAST is a fast heuristic method for sequence alignment and database searching. It works by first finding short words that are common between the query sequence and database sequences, and then extending the alignment around these words. BLAST is able to quickly search very large databases and find significant matches by calculating E-values, which estimate the statistical significance of matches. BLAST allows researchers to determine if a new sequence is similar to any known sequences and predict potential functions.
TrEMBL
TrEMBL is a computer-annotated protein sequence database created by Rolf Apweiler that contains translations of coding sequences from nucleotide databases like EMBL and GenBank as well as protein sequences from literature or submitted directly. The database provides automated classification and annotation to enrich the protein sequences.
Database in bioinformatics
A database is a structured collection of data that can be easily accessed, managed, and updated. It consists of files or tables containing records with fields. Database management systems provide functions like controlling access, maintaining integrity, and allowing non-procedural queries. Major databases include GenBank, EMBL, and DDBJ for nucleotide sequences and UniProt, PDB, and Swiss-Prot for proteins. The NCBI maintains many biological databases and provides tools for analysis.
Fasta
FASTA is a bioinformatics tool and biological database that is used to compare amino acid sequences of proteins or nucleotide sequences of DNA. It was first described in 1985 by Lipman and Pearson. FASTA performs fast homology searches to find similarities between a query sequence and sequences in a database. While similar to BLAST, FASTA is faster for sequence comparisons. It works by identifying patches of sequence similarity that may contain gaps. Some key FASTA programs include FASTA, TFASTA, FASTS, and FASTX/Y. FASTA is useful for applications like identification of species, establishing phylogeny, DNA mapping, and understanding protein function.
Nucleic Acid Sequence databases
This document discusses biological databases and nucleic acid sequence databases. It describes the three primary nucleotide sequence databases: GenBank, EMBL, and DDBJ. GenBank is hosted by the National Center for Biotechnology Information and contains over 286 million bases and 352,000 sequences. EMBL is hosted by the European Molecular Biology Laboratory and mirrors data daily with GenBank and DDBJ. DDBJ is the DNA Data Bank of Japan and also mirrors data daily with the other two databases. Biological databases are important tools for scientists to understand biology at multiple levels.
Cath
The CATH database hierarchically classifies protein domains obtained from protein structures deposited in the Protein Data Bank. Domain identification and classification uses both manual and automated procedures. CATH includes domains from structures determined at 4 angstrom resolution or better that are at least 40 residues long with 70% or more residues having defined side chains. Submitted protein chains are divided into domains, which are then classified in CATH.
Swiss PROT
SWISS-PROT- Protein Database- The Universal Protein Resource Knowledgebase (UniProtKB) is the central hub for the collection of functional information on proteins.
Prosite
The document discusses Prosite, a database of protein family signatures that can be used to determine the function of uncharacterized proteins. It contains patterns and profiles formulated to identify which known protein family a new sequence belongs to. The Prosite database consists of two files - a data file containing information for scanning sequences, and a documentation file describing each pattern and profile. New Prosite entries are mainly profiles developed by collaborators at the SIB Swiss Institute of Bioinformatics to identify distantly related proteins based on conserved residues.
Proteins databases
This document provides an overview of protein databases. It discusses the importance of protein databases for storing and analyzing protein sequence, structure, and functional data generated by modern biology. It summarizes several major public protein databases, including UniProt, NCBI RefSeq, PDB, InterPro, and Pfam, which contain protein sequences, structures, families, domains, and functional annotations. Searching and comparing sequences in these databases is an important first step in studying new proteins.
Introduction OF BIOLOGICAL DATABASE
Biological databases store and organize biological data and information. There are two main types - primary databases that contain original experimental data that cannot be changed, and secondary databases that contain derived data analyzed from primary sources. Examples of primary databases include GenBank for DNA sequences and SWISS-PROT for protein sequences. Secondary databases include PROSITE for protein families and domains, and Pfam for protein family alignments. Biological databases allow sharing of genomic and protein information worldwide and provide a foundation for research.
NCBI National Center for Biotechnology Information
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This document discusses the Basic Local Alignment Search Tool (BLAST), which allows users to compare a query DNA or protein sequence against sequence databases to find regions of local similarity. BLAST breaks the query into short words that are then searched for in database sequences. When words are found in common, BLAST extends the alignment in both directions to find higher-scoring matches. BLAST outputs include a graphical display of alignments, a hit list ranking matches by similarity score, and detailed alignments. BLAST has many applications, such as identifying species, establishing evolutionary relationships, DNA mapping, and locating protein domains.
protein data bank
The Protein Data Bank (PDB) is a single worldwide database that stores 3D structural data of proteins and nucleic acids. It is operated by Rutgers University, the San Diego Supercomputer Center, and the Research Collaboratory for Structural Bioinformatics. The PDB is freely accessible online and contains over 76,000 biomolecular structure entries as of 2011. It uses a common file format to represent structural data and is updated weekly as new entries are submitted by researchers.
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s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Nucleophilic Addition of carbonyl compounds.pptx
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
Cytokines and their role in immune regulation.pptx
This presentation covers the content and information on "Cytokines " and their role in immune regulation .
Nucleic Acid-its structural and functional complexity.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptx
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/Deep Software Variability and Frictionless Reproducibility
Deep Software Variability and Frictionless ReproducibilityUniversity of Rennes, INSA Rennes, Inria/IRISA, CNRS
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Bob Reedy - Nitrate in Texas Groundwater.pdf
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting
Equivariant neural networks and representation theory
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Unlocking the mysteries of reproduction: Exploring fecundity and gonadosomati...
The pygmy halfbeak Dermogenys colletei, is known for its viviparous nature, this presents an intriguing case of relatively low fecundity, raising questions about potential compensatory reproductive strategies employed by this species. Our study delves into the examination of fecundity and the Gonadosomatic Index (GSI) in the Pygmy Halfbeak, D. colletei (Meisner, 2001), an intriguing viviparous fish indigenous to Sarawak, Borneo. We hypothesize that the Pygmy halfbeak, D. colletei, may exhibit unique reproductive adaptations to offset its low fecundity, thus enhancing its survival and fitness. To address this, we conducted a comprehensive study utilizing 28 mature female specimens of D. colletei, carefully measuring fecundity and GSI to shed light on the reproductive adaptations of this species. Our findings reveal that D. colletei indeed exhibits low fecundity, with a mean of 16.76 ± 2.01, and a mean GSI of 12.83 ± 1.27, providing crucial insights into the reproductive mechanisms at play in this species. These results underscore the existence of unique reproductive strategies in D. colletei, enabling its adaptation and persistence in Borneo's diverse aquatic ecosystems, and call for further ecological research to elucidate these mechanisms. This study lends to a better understanding of viviparous fish in Borneo and contributes to the broader field of aquatic ecology, enhancing our knowledge of species adaptations to unique ecological challenges.
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PubMed
- 2. 2 What is PubMed PubMed Vocabulary Searching PubMed Advantages and disadvantages
- 3. What is PubMed ◉ PubMed is an interface for searching biomedical and life sciences journal articles and other related content ◉ PubMed was developed by National Centre for Biotechnology (NCBI) at the US. National Library of Medicine (NLM) located at the National Institute of Health (NIH). ◉ It was made accessible cost free to the world by former American Vice President AI Gore. It was made available to the public from 1996. 3
- 4. PM was developed from two journals 1. Proceedings of the National Academy of Sciences (PNAS) 2. Molecular Biology of the cell PMC mainly contain MEDLINE database of references and abstracts on life science and biomedical topics 4
- 5. PubMed is an index to articles published. An index contains bibliographic details of articles , the common details include about the ◉ Author ◉ Title ◉ Journal details ◉ Abstracts 5
- 6. PubMed Vocabulary ◉ Medical subject heading( MeSH) ◉ MeSh is the authority list of the vocabulary term used to index articles inside the data base. Its similar to a thesaurus of medical terms. • It is a vocabulary that gives uniformity and consistency to the indexing and cataloging of biomedical literature. • arranged in a hierarchical manner called the MeSH Tree Structures. • It is updated annually. 6
- 7. PubMed Website The PubMed website design and domain was updated on January 2020 and became default on 15 May 2020, with the updated and new features. The old PubMed is called Legacy PubMed. The latest PubMed website has new retrieval features : They have improved sensors of the word we have entered to search ◉ Search synonyms for the entered search ◉ Enhanced British/American mapping ◉ Truncate the terms which they find appropriate ◉ Result are provided based on best match 7
- 8. 8
- 9. Searching PubMed ◉ The PubMed website is made user friendly to facilitate easy search. ◉ Simple searching can be carried by entering key aspects of a subject into PubMed’s search window. PubMed translates this search adds fields names relevant MeSH, Boolain operators and MeSH terms. 9
- 10. What is the methodology for an efficient search 10
- 11. Searching PubMed ◉ ◉ In homepage we can search our topic. ◉ Advanced search option is available to get a more sophisticated result. 11
- 12. Searching PubMed ◉ The results obtained is called records in PubMed. ◉ It contains the citation. ◉ PubMed does not provide the full article. The article will be available through the published website 12
- 13. Filters 13
- 14. 14
- 15. 15
- 16. Result 16
- 17. Additional tools ◉ PubMed provides additional tools like ◉ Clinical queries ◉ Single citation matcher ◉ These tools help to search more efficiently 17
- 18. Advantages of PubMed ◉ Makes all contents free to read. It also provides copyright protection. ◉ It stores content in extensible Markup Language. PubMed represents the structure and meaning of a document in a relatively simple and human readable form. ◉ All the content is operated by NLM, it provides a framework to maintain copies of the PMC corpus. ◉ PubMed facilitated long term preservation of the scientific literature 18
- 19. Disadvantages of PubMed ◉ Citation searching is not available. ◉ It encourages superficial engagement with the literature. ◉ PubMed can be a dubious source of diagnostic assistance. 19
- 20. Reference ◉ https://mdanderson.libguides.com/pubmed ◉ Welch medical library , https://www.youtube.com/watch?v=1otz5qrUbxo ◉ https://pubmed.ncbi.nlm.nih.gov/about/ 20
- 21. THANKS! 21