Taxila search with logical operators:

To search in Taxila, you can use logical operators.

Taxila searches in the article tags, titles, and descriptions.
Current search handles terms separated by space “AND” as default.

Here is a complete list of all logical operators in Taxila:

Search Operator in Taxila

The search results are displayed in relevance order. That is, the articles which have a higher percentage of relevance will come first.
Let’s take an example where Article-1, whose total word count is100 and the search keyword frequency is 5, and Article-2 with the total word 1000, search keyword frequency is 10, then Article-1 would come at first in the search result list as it has higher relevance percentage.


From COVID-19 publications, you can check who is studying what subject via our analyzed network.

  1. Select [ANALAYSIS] menu on the top bar, and Select [Covid Scientist Chemical Network] from View Analysis panels.

Similar to other ANALYSIS viewers, you can navigate through the network.


From COVID-19 publications, you can check who is collaborating via our analyzed network.

  1. Select [ANALAYSIS] menu on the top bar, and Select [Covid Scientist Network] from View Analysis panels.

Clicking the [R] button on the left-bottom corner, and you can obtain the summary report of your selection as below.

In the top area, the counts of the selected articles, timeline and channels are displayed.

The most interesting part is the middle layer, which shows the trend of the most frequently used terms (tags). They are the lists of most frequently tagged terms of Chemicals, Biomolecules and Diseases.


COVID-19 Taxila now provides a new way to look at the terms in the articles.
This word galaxy view was generated by PubMed abstract on COVID-19 up to Jun 2020, and highlighted by categories, Genes, Chemicals, Symptoms, and Others.

Closer the terms positioned each other, the terms are more likely to appear in similar contexts/articles.

To get to view this galaxy analysis, go to [ANALYSIS] menu, then click [Covid Pubmed Abstract Galaxy].

You can click the help button on the right-top in the panel to learn how to navigate in the galaxy.

References

  • Adapted from Word Galaxy (https://github.com/anthonygarvan/wordgalaxy/ blob/master/index.html)
  • The site is maintained by SBX Corp. (http://www.sbx-corp.com)

By filtering the articles by Tags, then you can analyse the trends of tags/keywords in COVID-19Taxila collection.

  1. Click [KT] button on the left, then Taxila will move to the Trending Keywords analysis Panel.

We wanted to see how COVID-Taxila can quickly help us draw insights on the drug “Remdesivir” which has been proposed to be effective treatment strategy for covid-19.

40 Articles in the last 1 year on Remdesivir in Taxila

Four ways to filter the articles: Time Trends, Filter by Tags, Channel, Geo Trends

Filter By Time Window


Welcome to COVID-19 Taxila. When you log in, you see this landing page.

COVID-19 Taxila Portal

Read an Article with Tags

Let’s click on an article to read the abstract.
If you want to read fully from the source, you can click on the top-right corner.


Collect, curates and organizes COVID-19 research articles

In the context of COVID-19 pandemic, there is an urgent need to empower scientists, doctors and healthcare researchers at the frontline of the fight with access to the dynamic landscape of scientific literature, clinical trials and drug development efforts happening around the world.

Our team has developed the COVID-19-Taxila(https://covid19.taxila.io/) which collects, curates and organizes information on a daily basis from varied sources, including PUBMED, Arxiv, ClinicalTrials.gov, COVID-19 Open Research Datasets and others. It provides an easy-to-search interface for contextual navigation and a suite of analytics modules to enable the scientific community in obtaining actionable insights quickly.

We are providing the…

The Systems Biology Institute, Japan

The Systems Biology Institute (SBI), based out of Tokyo, is a non-profit private research institution established in 2000 by Dr.Hiroaki Kitano.

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