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diff --git a/BibliographicStudies.Rmd b/BibliographicStudies.Rmd
@@ -1,5 +1,5 @@
 ---
-title: "Bibliographic Studies"
+title: "Bibliometric Studies"
 subtitle: "Reproducible Bibliometric Analysis of Pathology Articles Using PubMed, E-direct, WoS, Google Scholar"
 author: "Serdar Balcı, MD, Pathologist"
 date: '`r format(Sys.Date())`'
@@ -25,6 +25,14 @@ output:
     toc_float: yes
 ---
 
+<a class="twitter-follow-button" data-show-count="false"
+  href="https://twitter.com/serdarbalci">Follow @serdarbalci</a><script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
+[![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/sbalci/PubMed/issues)
+[![Say Thanks!](https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg)](https://saythanks.io/to/sbalci)
+[![HitCount](http://hits.dwyl.io/sbalci/PubMed.svg)](http://hits.dwyl.io/sbalci/PubMed)
+
+
+
 # Introduction
 
 It is a very common bibliometric study type to retrospectively analyse the number of peer reviewed articles written from a country to view the amount of contribution made in a specific scientific discipline.

diff --git a/BibliographicStudies.nb.html b/BibliographicStudies.nb.html
diff --git a/README.Rmd b/README.Rmd
@@ -0,0 +1,41 @@
+---
+output: github_document
+---
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+# Reproducible Bibliometric Analysis of Pathology Articles
+### PubMed Indexed Peer Reviewed Articles in Pathology Journals: A country based comparison
+
+It is a very common bibliometric study to retrospectively analyse the number of peer reviewed articles written from a country to view the amount of contribution made in a specific scientific discipline.
+
+
+These studies require too much effort, since the data is generally behind paywalls and restrictions.
+
+
+I have previously contributed to a research to identify the Articles from Turkey Published in Pathology Journals Indexed in International Indexes; which is published here: http://www.turkjpath.org/summary_en.php3?id=1423 DOI: 10.5146/tjpath.2010.01006
+
+
+This study required manually investigating many excel files, which was time consuming and redoing and updating the data and results also require a similar amount of effort.
+
+
+In order to automatize this analysis, I have used PubMed data from National Library of Medicine (https://www.ncbi.nlm.nih.gov/pubmed/). This collection has the most comprehensive information about peer reviewed articles in medicine. It also has an API (https://dataguide.nlm.nih.gov/), and R packages are available for getting and fetching data from the server.
+
+
+Pathology Journal ISSN List data was retrieved from "in cites Clarivate", and Journal Data Filtered as follows: JCR Year: 2016 Selected Editions: SCIE,SSCI Selected Categories: 'PATHOLOGY' Selected Category Scheme: WoS
+
+
+Using these data I would like to make reproducible reports and shiny apps, not only on pathology field but also in other areas of medicine. This will be very useful to compare disciplines and different nations.
+
+---
+
+For updated analysis see: https://sbalci.github.io/pubmed/BibliographicStudies.html
+
+I would like to hear your feedback: https://goo.gl/forms/YjGZ5DHgtPlR1RnB3
+
+
+<a class="twitter-follow-button" data-show-count="false"
+  href="https://twitter.com/serdarbalci">Follow @serdarbalci</a><script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
+[![contributions welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/sbalci/PubMed/issues)
+[![Say Thanks!](https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg)](https://saythanks.io/to/sbalci)
+[![HitCount](http://hits.dwyl.io/sbalci/PubMed.svg)](http://hits.dwyl.io/sbalci/PubMed)
+
diff --git a/README.md b/README.md
@@ -1,28 +1,59 @@
-# Reproducible Bibliometric Analysis of Pathology Articles
-### PubMed Indexed Peer Reviewed Articles in Pathology Journals: A country based comparison
 
-It is a very common bibliometric study to retrospectively analyse the number of peer reviewed articles written from a country to view the amount of contribution made in a specific scientific discipline.
+<!-- README.md is generated from README.Rmd. Please edit that file -->
 
+# Reproducible Bibliometric Analysis of Pathology Articles
 
-These studies require too much effort, since the data is generally behind paywalls and restrictions.
+### PubMed Indexed Peer Reviewed Articles in Pathology Journals: A country based comparison
 
+It is a very common bibliometric study to retrospectively analyse the
+number of peer reviewed articles written from a country to view the
+amount of contribution made in a specific scientific discipline.
 
-I have previously contributed to a research to identify the Articles from Turkey Published in Pathology Journals Indexed in International Indexes; which is published here: http://www.turkjpath.org/summary_en.php3?id=1423 DOI: 10.5146/tjpath.2010.01006
+These studies require too much effort, since the data is generally
+behind paywalls and restrictions.
 
+I have previously contributed to a research to identify the Articles
+from Turkey Published in Pathology Journals Indexed in International
+Indexes; which is published here:
+<http://www.turkjpath.org/summary_en.php3?id=1423> DOI:
+10.5146/tjpath.2010.01006
 
-This study required manually investigating many excel files, which was time consuming and redoing and updating the data and results also require a similar amount of effort.
+This study required manually investigating many excel files, which was
+time consuming and redoing and updating the data and results also
+require a similar amount of effort.
 
+In order to automatize this analysis, I have used PubMed data from
+National Library of Medicine (<https://www.ncbi.nlm.nih.gov/pubmed/>).
+This collection has the most comprehensive information about peer
+reviewed articles in medicine. It also has an API
+(<https://dataguide.nlm.nih.gov/>), and R packages are available for
+getting and fetching data from the server.
 
-In order to automatize this analysis, I have used PubMed data from National Library of Medicine (https://www.ncbi.nlm.nih.gov/pubmed/). This collection has the most comprehensive information about peer reviewed articles in medicine. It also has an API (https://dataguide.nlm.nih.gov/), and R packages are available for getting and fetching data from the server.
+Pathology Journal ISSN List data was retrieved from “in cites
+Clarivate”, and Journal Data Filtered as follows: JCR Year: 2016
+Selected Editions: SCIE,SSCI Selected Categories: ‘PATHOLOGY’ Selected
+Category Scheme: WoS
 
+Using these data I would like to make reproducible reports and shiny
+apps, not only on pathology field but also in other areas of medicine.
+This will be very useful to compare disciplines and different nations.
 
-Pathology Journal ISSN List data was retrieved from "in cites Clarivate", and Journal Data Filtered as follows: JCR Year: 2016 Selected Editions: SCIE,SSCI Selected Categories: 'PATHOLOGY' Selected Category Scheme: WoS
+-----
 
+For updated analysis see:
+<https://sbalci.github.io/pubmed/BibliographicStudies.html>
 
-Using these data I would like to make reproducible reports and shiny apps, not only on pathology field but also in other areas of medicine. This will be very useful to compare disciplines and different nations.
+I would like to hear your feedback:
+<https://goo.gl/forms/YjGZ5DHgtPlR1RnB3>
 
----
+<a class="twitter-follow-button" data-show-count="false"
+  href="https://twitter.com/serdarbalci">Follow
+@serdarbalci</a>
 
-For updated analysis see: https://sbalci.github.io/pubmed/BibliographicStudies.html
+<script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script>
 
-I would like to hear your feedback: https://goo.gl/forms/YjGZ5DHgtPlR1RnB3
+[![contributions
+welcome](https://img.shields.io/badge/contributions-welcome-brightgreen.svg?style=flat)](https://github.com/sbalci/PubMed/issues)
+[![Say
+Thanks\!](https://img.shields.io/badge/Say%20Thanks-!-1EAEDB.svg)](https://saythanks.io/to/sbalci)
+[![HitCount](http://hits.dwyl.io/sbalci/PubMed.svg)](http://hits.dwyl.io/sbalci/PubMed)
diff --git a/Sources.Rmd b/Sources.Rmd
@@ -183,6 +183,10 @@ https://www.sciencemag.org/news/2017/05/vast-set-public-cvs-reveals-world-s-most
 
 ## Semantic Scholar
 
+https://www.semanticscholar.org/
+
+
+### Semantic Scholar Open Research Corpus
 
 ```
 Semantic Scholar Open Research Corpus
@@ -197,6 +201,26 @@ caffeinate
 
 ```
 
+### AllenNLP
+
+https://allennlp.org/
+
+
+### An open-source NLP research library, built on PyTorch.
+
+http://www.allennlp.org/
+
+https://github.com/allenai/allennlp
+
+
+### citeomatic
+
+https://allenai.org/semantic-scholar/citeomatic/
+
+
+
+
+
 ## Microsoft Academic
 
 https://labs.cognitive.microsoft.com/en-us/project-academic-knowledge
@@ -292,6 +316,27 @@ https://www.lens.org/lens/scholar/search/results?q=(author.affiliation.name:%20%
 https://www.lens.org/lens/scholar/search/analysis?q=(author.affiliation.name:%20%22neurosurgery%22%20%20OR%20author.affiliation.name:%20%22sport%22%20)%20AND%20(abstract:%20%22sport%22%20%20OR%20title:%20%22sport%22)&page=0&limit=10&orderBy=%2Bscore&dateFilterField=year_published&preview=false&regexEnabled=false
 
 
+```
+my_data_frame <- readr::read_delim("~/downloads/pubmed_result.txt", delim = "\t", col_names = FALSE)
+
+chunk <- 5000
+mylist <-  split(my_data_frame, rep(1:ceiling(nrow(my_data_frame)/chunk), each=chunk, length.out=nrow(my_data_frame)))
+
+X1 <- mylist$`1`
+X2 <- mylist$`2`
+X3 <- mylist$`3`
+X4 <- mylist$`4`
+
+readr::write_csv(X1, "~/downloads/1.txt")
+readr::write_csv(X2, "~/downloads/2.txt")
+readr::write_csv(X3, "~/downloads/3.txt")
+readr::write_csv(X4, "~/downloads/4.txt")
+
+```
+
+
+
+
 #### PatCite
 
 
@@ -346,10 +391,62 @@ https://europepmc.org/downloads
 https://elixir-europe.org/platforms/data/core-data-resources
 
 
+---
+
+## scite
+
+
+https://scite.ai/
+
+
+---
+
+## TÜBİTAK Destekli Projeler Veri Tabanı
+
+Ülkemizdeki araştırma altyapısına katkı sağlamak amacıyla, Araştırma Destek Programları Başkanlığı (ARDEB) bünyesinde, 1965 yılından günümüze kadar sonuçlanmış olan 17.808 adet projenin sonuç raporunun tam metinleri, TÜBİTAK Ulusal Akademik Ağ ve Bilgi Merkezi (ULAKBİM) “TÜBİTAK Destekli Projeler Veri Tabanı”nda yayımlanmaktadır.
+
+
+Söz konusu veri tabanına https://trdizin.gov.tr/search/projectSearch.xhtml linkinden erişim sağlanabilmekte ve sonuç raporlarına ilişkin proje no, başlık, yürütücü/araştırmacı/danışman adı, yıl ve anahtar kelime bazında tarama yapılabilmektedir.
+
+
+## TRDizin
+
+https://trdizin.gov.tr/
+
+
 ---
 
 # Software
 
+
+## R-project
+
+https://github.com/schochastics/graphlayouts
+
+
+### rentrez
+
+```
+https://github.com/ropensci/rentrez/issues/134#event-2313355730
+
+library(rentrez)
+library(XML)
+
+MeSH_from_pmid <- function(pmid){
+   rec <- entrez_fetch(db="pubmed", id=pmid, rettype = "xml", parsed=TRUE)
+   m_names <- xpathSApply(rec, "//MeshHeadingList/MeshHeading/DescriptorName", xmlValue)
+   m_ui <- xpathSApply(eg_rec, "//MeshHeadingList/MeshHeading/DescriptorName", xmlAttrs)[1,]
+   data.frame(mesh_ui = m_ui, descriptor = m_names)
+}
+
+MeSH_from_pmid(27591765)
+
+
+
+```
+
+
+
 ## CiteSpace
 
 - CiteSpace Tutorial