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Engineering » Biomedical Engineering » "Biomedical Engineering - From Theory to Applications", book edited by Reza Fazel-Rezai, ISBN 978-953-307-637-9, Published: August 29, 2011 under CC BY-NC-SA 3.0 license. © The Author(s).

Chapter 1

Biomedical Web, Collections and Meta-Analysis Literature Applications

By Layla Michán, Israel Muñoz-Velasco, Eduardo Alvarez and Lyssania Macías
DOI: 10.5772/18133

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The resource’s classification for retrieval biomedical information.
Figure 1. The resource’s classification for retrieval biomedical information.
Process for retrieval information.
Figure 2. Process for retrieval information.
Chrome personalized browser for biomedical literature retrieval.
Figure 3. Chrome personalized browser for biomedical literature retrieval.
The Most popular scientific search engines. General search, retrieval from 16 February 2011, *Papers published in journals
Table 1. The Most popular scientific search engines. General search, retrieval from 16 February 2011, *Papers published in journals
The most popular databases for biomedical literature (Date of access: March 2011)
Table 4. The most popular databases for biomedical literature (Date of access: March 2011)

Biomedical Web, Collections and Meta-Analysis Literature Applications

Layla Michán, Israel Muñoz-Velasco, Eduardo Alvarez and Lyssania Macías

1. Introduction

Cause and effect of the digital revolution is the production of a lot and different kinds of web tools, applications and resources that permit optimization the retrieve, management and analysis of biomedical bibliography. The information revolution is a cause and effect of scientific and technological progress of the twentieth century, amount of information that is now produced on different scientific topics is huge plus: It can be electronic or printed, there is text, images and sounds is systematized in databases data, catalogs or lists, your query can be free or restricted, is on life or their parts, phenomena and explanations, cover publications, researchers, projects, groups and research lines, agreements, grants, scientific, institutions research and teaching, biological collections, educational institutions and societies science, to name a few. Refer to information in the twenty-first century involves the mention of terms, methods, novel and innovative theories as knowledge society, information society, globalization, info diversity, access to information, e-science, e-research, grid, collaboratories, repositories, knowledge based on literature, text mining, semantic web, impact index, cocitation, web 2.0 and 3.0, social networking, plagiarism, and free access. Those changes have been dramatically impacted the contemporary world view, scientific practice and scientific relations, social, economic, political and cultural (Russell, 2001).

Scientific society generates and receives information, it is exposed to it as a representation of thought and knowledge in all cases creates a conscious or unconscious interest transmits individually or collectively. The scientific communities recognize the value of the information, required it as a condition to perform fundamental research. Published information on biology and medicine is not exception, the quantity, diversity and complexity of digital information are so many and so different, some electronic resources through which you can access it are not simple, which has made it necessary to be informed and update on the continuing emergence and modification of these tools, while it has become a problem to solve: continuously published magazines in a large number of items. Recover strategies and analysis of information on the specific area of interest of researchers and design programs and websites constantly to achieve this (Larson, 2010a).

Electronic resources with biomedical literature can be consulted electronically Internet allows instant access to digital data collections updated with information generated by the specialists (Faciola, 2009). The power of the new electronic technologies has increased exponential, we have designed a lot of applications that allow you to group, sort and display documents which have reduced power, cost and time required to analyze literature specialized (Hey & Trefethen, 2005). Not only that, in less than ten years has changed the practice of science, is no longer explores the reality only through experiments and models in vivo and / or in vitro but made in silico tools and computational methods (Atkins et al., 2003). This phenomenon has affected both the way we produce scientific knowledge that have developed new fields of knowledge practiced by specialists, such as bioinformatics, medical informatics, biological informatics, neuroinformatics, and literature-based discovery, among others. The change has been important even in the way recovered and analyzed the literature so much that you have proposed new ways to access the information to put aside the reductionist approach and adopt a system according to the progress of own biological discipline.

The search, access, analysis and updating of the literature in databases has become a daily task. It is usually necessary to consult several indexes to have more complete representation of the literature on the topic of interest (Zhou et al., 2006). But such is the quantity and diversity of papers on biomedicine, there are so many, so different and complex electronic resources (especially bibliographic databases) through which you can access that information, not just that, but change, progress and constantly updated, it is difficult to keep track of them all and identify which and how many can and should use.

2. Biomedical web

The Biomedical Science is one of the most innovative and cutting-edge in science, excellence and is recognized today. The literature in this field is applied in several biomedical practice areas, ranging from the production of new biological knowledge to resource management, assessment, management and science policy (Labarga, 2009). For these reasons essential to include an innovative course in art, sort and classify all electronic resources for the recovery and analysis of specialized information effectively and efficiently, in a review of the types and characteristics of digital information, explaining definitions basic, to explore its importance and implications, are synthesized and explain the electronic resources online more relevant and practical, especially databases and specialized software, are presented source’s compendiums from which information can be extracted and understanding (Rizkallah & Sin, 2010; Weeber et al., 2005; Henderson, 2005) like scientometrics studies (Cokol & Rodriguez-Esteban, 2008; Uthman, 2008; Li et al., 2009; Boyack, 2004).

Also allow stakeholders to introduce the necessary tools to make reports to information and documents indexed journals, impact, collaboration and citation of own production commonly requested by the evaluation committees of National Foundations and councils.

This chapter presents the application of an interdisciplinary and integrative approach to use biomedical literature to extract, analyze and manage specialized literature efficient, prompt, timely, comprehensive and organized.

Contrary to common understanding now exist a lot of friendly electronic tools for non informatics specialist’s that permit literature Biomedicine management, designed from informatics specialist’s to all others. Previous knowledge it’s not needed to use this web tools and services (Hull, et al., 2008; Renear, & Palmer, 2009). Most of them are open access resources. Some of their advantages are:

  1. Explain in detail the cyberinfrastructure (resources, tools and services) available for the management of literature specializes in biomedicine, keeping with the needs and challenges of our time and explains the characteristics of each, Biomedicine.

  2. Present the stages of document retrieval electronics and how to handle this is done in an efficient, effective and updated.

  3. State the main bibliometric indicators are frequently used to evaluate literature.

  4. Apply new techniques to analyze the references, the contents of scientific papers and large quantities of documents simultaneously, including network analysis and discovery based on the literature.

In this chapter we will classify, systematize and describe the most useful web-based applications for innovative retrieval and processing of biomedical literature; all of them are friendly and can be used by any scholar or biomedical specialist. We will present all resources in three categories: 1) general web applications, 2) literature collections and 3) meta-analysis tools in logic retrieval and processing literature order (Fig. 1).


Figure 1.

The resource’s classification for retrieval biomedical information.

2.1. Web literature retrieval

Digital information retrieval from the Web, in a modern sense is a personalized, automatic, multitask, integrated and immediacy process (Larson, 2010b) the stages of document retrieval electronics and how to handle this is done in an efficient, effective and updated form with specific apps. The process consists of: search (browser, search engines and collections), bookmark (Bookmarks), manage (reference management) share and analyze (Meta-analysis apps).

Every day a lot of innovative web apps appeared with Biomedical scholar interest like web pages, wikis, blogs and search engines (web 2.0 and web 3.0), social networks, feeds, reference management software and mobile resources, the most relevant for biomedicine.


Figure 2.

Process for retrieval information.

The process for retrieve literature on the web begins with the web browser, the Merriam-Webster's dictionary (2011) defines a web browser as a computer program used for accessing sites or information on a network (as the World Wide Web). This is a simple, yet accurate description. Web browsers come in many different styles, each with their own nuances. However, the main reason a person utilizes a web browser is to view web pages on the Internet, similar to the way you are viewing this book right now. Today there are the two main open source web browsers with add-on options (something as an accessory or added feature that enhances the thing it is added to) that the search experience, Firefox from Mozilla ( and Chrome from Google ( (Fig. 3), right now our favorite is the second one, because is easy and speed, but right now the first one has the most bigger gallery of complement options.

There are a lot of resources, tools and services available for the management of literature Biology specializes in keeping with the needs and challenges of our time, the most efficient could be installed in the browser for better and faster use.


Figure 3.

Chrome personalized browser for biomedical literature retrieval.

2.1.1. Search engines and meta-searchers

There are thousands of search engines in the Internet, a program that searches documents for specified keywords and returns a list of the documents where the keywords were found. They create a web pages database that use any algorithm to classify the web pages (wikis, blogs, sites, …), the most biggest and also the most used for general research are Google, Bing, Yahoo, Altavista, Lycos, and Ask. But there are some scholar biomedical search engines that filter and index specialized and certified web pages like Scirus, Scientific WebPlus, Orefil, Nextbio or Quertle (Table 1).


Table 1.

The Most popular scientific search engines. General search, retrieval from 16 February 2011, *Papers published in journals

2.2. Biomedical collections

Computing tool of choice for systematizing the documents and metadata are the databases, a computerized bibliographic records stored in tables with an established order that allows you to save, sort, retrieve and generate information. We will divide the main biomedical literature collections in five kinds: 1) Libraries, 2) Information systems, 3) Index and catalogs, 4) Bookstores or editorials (press) and 5) Repositories. We classified a sample of each one.

Literature CollectionExampleURL
Information systemEntrez
Paper index o catalog,
Journal index o catalog
Journals NCBI
PressBiomed Central
RepositoryPubMed central

Table 2.

Kinds of biomedical collections

A digital library (e-Library) comprises digital collections, services and infrastructure to support lifelong learning, research, scholarly communication and preservation and conservation of our knowledge recorded and democratization, has a clear goal and are formed with a selection of content organized through a descriptive metadata (cataloging) and also associated with some facilities for search and use of services (Borgman, 1999), makes use of telecommunications and particularly the Internet to facilitate access to its contents remotely or locally through various connected systems that provide control and preservation of resources, while providing added services around the needs of users and information collected managed and preserved.

If a Web application allows you to consult more than one library collection simultaneously, we have named the information system (Villanova-Oliver et al., 2003). We define all information collection systematized into a digital database with immediate access, designed with the intention of making them available for those interested in his consultation with academic and made available through the Web.

We define also a library collections or literature as all those documents that record information about scientific research product is the result of a process of planning and balanced acquisition of library materials in various formats, mainly primary literature consists of books, magazines and conference proceedings, online resources, and other media, bibliographies, references, stored, structured and inter-linked for retrieval using a computer system.

Press is the process of production and dissemination of literature or information, the activity of making information available for public view. In some cases, authors may be their own publishers, meaning: originators and developers of content also provide media to deliver and display the content. Traditionally, the term refers to the distribution of printed works such as books (the "book trade") and newspapers. With the advent of digital information systems and the Internet, the scope of publishing has expanded to include electronic resources, such as the electronic versions of books and periodicals, as well as micropublishing, websites, blogs and video games.

There is necessary for a better information retrieval to know the main characteristics of the datasets for search like temporal coverage, geographic coverage, topic coverage, size coverage and typological coverage. For better understand we present a key card with the dissection of PubMed the most used bibliographic biomedical database (Table 3).

Editor/ProducerNational Center for Biotechnology Information, U.S. National Library of Medicine.
Typological coverageScientific articles, online books, case reports, clinical conferences, clinical trials, comparative studies, conferences, commentaries, dictionaries, directories, editorials, evaluation studies, government publications, historical articles, interactive tutorials, interviews, letters, newspaper articles, revisions, retractions of publications, technical reports, twin studies, web-cast. Is accompanied by other resources contained in other databases under the responsibility of NCBI as sequences of genes and proteins, and analysis.
Subject coverageBiomedical and life sciences. As well as dentistry, nursing, veterinary, pharmaceutical, and other related.
Temporal coverage1951
Start date1997
Geographical coverage“World” (70 countries)
Language of documentsUsually in English. Also French, German, Italian, Japanese, Russian, Spanish, Albanian, Catalan, Korean, Polish, Portuguese, Romanian, Serbian, Slovenian, Turkish, and Vietnamese among others.
ThesaurusYes, through MeSH.
Total recordsJournals: 23,000.
Records: 20 million.
UpdateEvery 2 days
Number of records displayed per page5, 10, 20, 50, 100 y 200
Access full textYes, when the document is freely available, is in PubMed Central, or have the relevant subscription to the journal.
Search fieldsTitle, abstract, author, book, corporate author, creation date, number EC / RN, editor, filter, first author, author's full name, full name of investigator, ISBN, issue, volume, journal, language , last author, ID, location, name of substances.
Save the queryIf you have a My NCBI account.
Advanced searchAffiliation [AD]
Article Identifier [AID]
All Fields [ALL]
Author [AU]
Book [book]
Comment Corrections
Corporate Author [CN]
Create Date [CRDT]
EC/RN Number [RN]
Editor [ED]
Entrez Date [EDAT]
Filter [FILTER]
First Author Name [1AU]
Full Author Name [FAU]
Full Investigator Name [FIR]
Grant Number [GR]
Investigator [IR]
Issue [IP]
Journal Title [TA]
Language [LA]
Last Author [LASTAU]
Location ID [LID]
MeSH Date [MHDA]
MeSH Major Topic [MAJR]
MeSH Subheadings [SH]
MeSH Terms [MH]
NLM Unique ID [JID]
Other Term [OT]
Pagination [PG]
Personal Name as Subject [PS]
Pharmacological Action MeSH Terms [PA]
Place of Publication [PL]
Publication Date [DP]
Publication Type [PT]
Secondary Source ID [SI]
Subset [SB]
Substance Name [NM]
Text Words [TW]
Title [TI]
Title/Abstract [TIAB]
Transliterated Title [TT]
Volume [VI]
Export recordsYes, via e-mail and bibliography managers EndNote, Reference Manager, and ProCite.
Citation analysis No.
List of journal indexedYes, by downloading a file.
Displayed documents referencesNo
Links to full text electronic documentYes
Search by keywordNo
Interface languageEnglish
Related documentYes
Web 2.0 appsRSS, bookmarks, alerts, saved search results by e-mail.
Document selection criteria Is based on the magazine
Coverage: Articles mainly on basic biomedical research.
Quality: validity, relevance, originality and contribution to the field coverage of content.
Editorial quality, objectivity, credibility and quality of its contents, peer review, ethical quality, timely correction of errors.
Production Quality: Design, printing, graphics and illustrations (but not pre-requisite)
Audience: health professions: researchers, practitioners, educators, administrators and students.
Content type: Reports of original research, original clinical observations accompanied by analysis and discussion, analysis of philosophical, ethical, social or health professions or biomedical sciences, critical commentaries, statistical compilations, descriptions of evaluation methods or procedures, case reports with discussions.
Language: At least title and abstract in English.
Geographic coverage: Generally not be selected for indexing if the contents are subjects already well represented in MEDLINE or published to a local audience.
Records meta-analysis*No
ToolsMy NCBI.
Save searches, results, bibliography, and has an automatic update option.
My NCBI preferences.
Storage, highlight search terms, abstract screen, additional data.
Furthermore, filtering of search results, view recent activity and the establishment of Link Out, document delivery service.
AdvantagesDatabase more important, most used, most popular in biomedical information. Very short time to upgrade. It is complemented with other resources and information bases by the NCBI. Using multiple and varied fields of search.
DisadvantagesFew or no options for meta-analysis. Ambiguity in the identification of authors and documents.

Table 3.

Characteristics of PubMed database. *Meta-analysis details are explained below.

Index and catalog. Although the biomedical community uses mainly PubMed database for literature retrieval, there are a lot of restricted/open, regional/global and monothematic/multithematic collections that are important to obtain an exhaustive review of the publisher papers. There are more useful catalogs: with documents and journals (Table 4).


Table 4.

The most popular databases for biomedical literature (Date of access: March 2011)

The Merriam Webster dictionary (2011) defines a repository as one that contains or stores something nonmaterial<considered the book a repository of knowledge>. Repositories of literature are understood as large files that store digital texts composed of a group of services designed to capture, store, manage, preserve and redistribute the documentation to a certain audience or a specific user community (Pappalardo and Fitzegerald, 2007). Emerged from the so-called e-print community, concerned to maximize the spread and impact of scientific works deposited in them (Melero, 2005). An e-print (e-paper) is the digital version of a research paper (usually a journal article, but could be a thesis, papers, book chapters, or book) is available online because it has been deposited in a digital repository (Swan and Brown, 2005), which comprises five components essential to its operation: interactivity, design, integration, aggregation and mobility. Digital versions of research papers called e-prints include both pre-prints (articles before they are evaluated by peers) and post-prints (version result of peer review).

Repositories whose main function the storage of files and their creation is linked with the movement of information from open access (open access), a term that describes the online public access without restriction to scientific articles (Suber et al., 2010 ), has two forms: free and open. Repositories are dynamic tools, consisting of the infrastructure, programs, personal information and keeping it and consultation. They constantly recorded and scholars put their scientific production, as are the basic units of construction of the global scholarly communication, and therefore of scientific collaboration (Table 5).

RepositoryKindTotal Records
PubMed Central
National2 million articles
PubMed UK
National1.8 million full text, peer reviewed published journal articles covering all fields of biomedical and health research (the UK PubMed Central repository)
24 million PubMed and PubMed Central abstracts
Dspace MIT
Institutional47,133 titles
2,500 scholar articles
25,000 theses completed

Table 5.

The biggest repositories

2.3. Automatic meta-analysis apps

We will present in meta-analysis topic around five dozens of web applications that process thousands of bibliographic records simultaneously, automatic and instantaneous for patterns identification, visualization or better retrieval goals. Apply new techniques of analysis of the references and the contents of scientific papers to analyze large quantities of documents simultaneously, including bibliometrics, text mining, semantic or networks analysis (Table 6).

BibliometricsBibliometrics involves the quantitative assessment of certain events in the literature and therefore scientific literatures, main bibliometric indicators (publication counts, impact factors and received citations, for example) are frequently used to retrieve and evaluate literature (Koskinen et al., 2008). In this way the bibliometric analysis is a good tool to assess the impact of an investigation in the context of others scientific investigations and it’s possible compares the relative contributions of research groups or institutions, infer patterns and trends (Rosas et al., 2011).
Text miningText mining involves the processes of information retrieval, automated information extraction and data mining from electronically published sources. It is used to generate new knowledge interesting, plausible, and intelligible (Ananiadou et al., 2006).
Linking two or more literature concepts that have so far not been linked (i.e., disjoint) through the use of software and algorithms designed for this purpose (Rodriguez-Esteban, 2009).
To perform text mining, it must be structured (pre-processing) to analyze texts or discovering interesting patterns that generate new knowledge (Krallinger et al., 2008). Depending on the methods used in the pre-processing is the type of representation of the contents of the texts constructed, and according to this representation, is the kind of patterns discovered (Harmston et al., 2010).
SemanticBased on the ontologies, that formulate a conceptual scheme (a map of concepts and their relationships) in a given domain, the semantic expresses the meaning of data, the properties of objects and the complex relationships between them by a series of formal rules (Robu et al., 2006).
Networks analysisNetworks are open structures that can expand without limit of integration of new nodes based on the communication possibilities that exist in your environment and share communications code compatible.
It is done through the study of theories of structural behavior, the dynamics, and influence within the biomedical issues, to establish a likely explanation for the growth and evolution of real networks in any advanced biomedical subject.

Table 6.

Most frequent literature automatic meta-analysis methods.

Right now exist dozens of scholar free web programs that process literature with one or more bibliographic meta-analysis methods. Most of those resources are based on PubMed literature because it is open access records, normalized and robustness information. For this chapter we choose some of them for details, a list with most of them is in Append.

2.3.1. Bibliometric analysis



HubMed ( retrieval information from the PubMed´s database and produces one interface focused basically on browsing, organizing and gathering information from the biomedical literature. Shows the results arranged by relevance, you can perform grouping and graphic representation of related articles, can export metadata in different formats for further analysis.



Twease is a web-based tool to search in the abstracts for Medline. Index the words of Medline and provides features to expand a query and thereby find what you are looking for. Finally, Twease can automatically discover common abbreviations for search phrases.(;jsessionid=2ACC96312364DDB1E50519CE8EC316BB?component=clearSettingsDirectLink&page=Home&service=direct&session=T)

2.3.2. Text-mining



PubReMiner ( process the results of a query based in PubMed´s database and display its results in frequency tables, get all abstracts and generate metric statistics that include journals, authors and most productive countries, analyze your query words in the title, abstract, keywords and name of substances, allows extract metadata for further metric analysis.



Application that is known for scoring the key terms in the abstracts of articles and predict the relationships between key terms from biomedical literature into four categories: genes, chemicals, diseases and organs.

Also performs statistical analysis of co-citation of annotated key terms to infer relationships (

2.3.3. Ontology-based literature search (semantic)

Go PubMed


Search PubMed for biomedical research articles ( Your keywords are submitted to PubMed and the resulting abstracts are classified using Gene Ontology and Medical Subject Headings (MeSH).

MeSH is a hierarchical vocabulary covering biomedical and health-related topics.

GeneOntology is a hierarchical vocabulary for molecular biology covering cellular components, biological processes and molecular functions.

PIKB: Pathways and Interaction Knowledge Base


PIKB ( allows you to execute arbitrary queries in the semantic network. For example: "Select pathways controlled by the expression of genes located in a specific chromosome". You can also use sets of declarative rules to customize the criteria for identifying redundant information. For example: "All molecular interactions composed by a related Uniprot accession number, a Uniprot cross-reference identifier or an Entrez-Gene identifier and coming from different data sources are equivalent".

2.3.4. Networks analysis

Ali Baba PubMed


Shows the connection of separate record of terms such as cells, drugs, tissues, diseases, reactions, enzymes and compounds of the KEGG (Kyoto encyclopedia of genes and genomes), nutrients, proteins and genes, UniProt and NCBI Taxonomy species. Once the sample has identified links of the articles found as protein-protein interactions, localization of proteins, nutrients and genes (


Find the proteins and genes related documents. It shows the quantity of items for each node and its relationships (

3. Conclusion

The use of web apps investigated in this work makes it possible to extract, analyze and manage an automated literature, efficient, prompt, timely, comprehensive and organized to facilitate handling of large amounts of documentary records simultaneously, choose from the vast amount of the most relevant information available, handle the selected records and learn the ways of analysis of latest digital literature, from which it can and must extract information according to the needs and challenges of our time. Because the constantly actualization and the release of new and innovative internet tools, we have a blog with news about Biomedical Web, Collections and Meta-Analysis Literature Applications:


Roberto Calderón for retrieval information and discussions, Claudia Itzel Pedraza for some data about retrieval information, Jack Guillén, Teresita Amezcua and Francisco Castillo for revisions and corrections to the text.

Founds DGAPA, UNAM Project PAPIME PE 201509 and CONACYT 13276.

4. Append

Web apps that process literature with one or more bibliographic meta-analysis methods

Batch Citation Matcher

PubMed Retractions

e-LiSe - text mining tool for Medline data - run

eGIFT - extracting Gene Information From Text

Biomedical Informatics Group : PubDNA Finder

BOND Web Portal

eGIFT - extracting Gene Information From Text

MEDSUM - THE MEDLINE/PubMed SUMMARY TOOL: research PubMed and Medline data

Meva - MedLine Postprocessor


BioText: Project Homepage

BITOLA - Biomedical Discovery Support System


FABLE - Fast Automated Biomedical Literature Extraction


MEDIE - Semantic retrieval engine for MEDLINE


MedMiner - MetaBase


XplorMed: eXploring Medline abstracts


Skill Kit: Searching Full Author Names in PubMed. NLM Technical Bulletin. 2009 Mar–Apr

NCBI ESpell Utility


PubMed Tools

Home - PubMed Alternatives - Research Guides at Virginia Commonwealth University

PubMed On Tap

Unbound MEDLINE | Free MEDLINE/PubMed Journal Article Search


EGQuery Entrez Utility

Pubget: the search engine for life-science PDFs

Taxonomy Home

medical Subject Headings (MeSH)

PubSearch Fast, efficient PubMed® searching on your Mac and your iPhone / iPod Touch

Deja vu


ARMiner Info Index

PubGene. Browse literature or sequence neighbours.

Kleio @ NaCTeM

Acromine dictionary




NLM Mobile

Pubget Mobile

MD on Tap

Bionlp search page

University of Geneva - EAGL System

LitLinker - Home

Telemakus Home


Anne O'Tate


PubMed Gold

< MEDLINE/PubMed Multilanguage Search

PubMed global biomedical research community - BioWizard

BITOLA - Biomedical Discovery Support System

PubCrawler Web Service


iHOP - Information Hyperlinked over Proteins

NCBO BioPortal: Welcome to the NCBO BioPortal


Home - BioMedLib™ search engine

BioIE - Extracting informative sentences from the biomedical literature

PubMed Assistant

e-LiSe - text mining tool for Medline data

FACTA - Finding Associated Concepts with Text Analysis

FABLE - Fast Automated Biomedical Literature Extraction

Journal / Author Name Estimator

Ali Baba — PubMed as a graph

PubNet: Publication Network Graph Utility

Pubget: the search engine for life-science PDFs

PolySearch: a web-based text mining system for...

Deja vu > Browse

Non-Bibliographic LinkOut Providers

Bio Saga: 18 Ways to improve your PubMed searches


Manjal - Mining MEDLINE for New Ideas


PubMed search: A free individualized PubMed software search

Anne O'Tate


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