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A repository of web-based bioinformatics resources developed in India

Agarwal, A.; Agrawal, P.; Sharma, A.; Kumar, V.; Mugdal, C.; Raghava, G. P. S.

2020-01-23 bioinformatics
10.1101/2020.01.21.855627 bioRxiv
Show abstract

IndiaBioDb (https://webs.iiitd.edu.in/raghava/indiabiodb/) is a manually curated comprehensive repository of bioinformatics resources developed and maintained by Indian researchers. This repository maintains information about 543 freely accessible functional resources that include around 258 biological databases. Each entry provides a complete detail about a resource that includes the name of resources, web link, detail of publication, information about the corresponding author, name of institute, type of resource. A user-friendly searching module has been integrated, which allows users to search our repository on any field. In order to retrieve categorized information, we integrate the browsing facility in this repository. This database can be utilized for extracting the useful information regarding the present scenario of bioinformatics inclusive of all research labs funded by government and private bodies of India. In addition to web interface, we also developed mobile to facilitate the scientific community.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 16%
11.9%
Similar papers in this journal
2
F1000Research
○ 88 papers in training set
Top 0.1%
6.7%
Similar papers in this journal
3
Genomics
○ 64 papers in training set
Top 0.1%
5.2%
Similar papers in this journal
4
PeerJ
◐ 308 papers in training set
Top 1%
4.4%
Similar papers in this journal
5
Briefings in Bioinformatics
◐ 354 papers in training set
Top 2%
4.0%
6
GigaScience
◐ 212 papers in training set
Top 0.9%
4.0%
7
BMC Research Notes
○ 33 papers in training set
Top 0.1%
4.0%
Similar papers in this journal
8
BMC Bioinformatics
○ 457 papers in training set
Top 2%
3.5%
9
Database
◐ 61 papers in training set
Top 0.2%
3.5%
10
PLOS Computational Biology
● 1863 papers in training set
Top 10%
3.2%
50% of probability mass above
11
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 1%
3.2%
12
PROTEOMICS
○ 43 papers in training set
Top 0.2%
3.2%
13
Scientific Reports
○ 3612 papers in training set
Top 34%
3.2%
14
Gigabyte
● 62 papers in training set
Top 0.4%
2.6%
15
Frontiers in Genetics
○ 230 papers in training set
Top 1%
2.6%
16
Informatics in Medicine Unlocked
○ 22 papers in training set
Top 0.4%
2.1%
17
Gene Reports
○ 14 papers in training set
Top 0.3%
1.7%
18
BMC Genomics
○ 406 papers in training set
Top 4%
1.7%
19
Journal of Bioinformatics and Systems Biology
○ 15 papers in training set
Top 0.1%
1.1%
20
BMC Medical Genomics
○ 50 papers in training set
Top 0.9%
1.0%
21
Heliyon
○ 152 papers in training set
Top 7%
1.0%
22
Biochimie
○ 25 papers in training set
Top 0.6%
0.9%
23
Bioinformatics
◐ 1204 papers in training set
Top 9%
0.8%
24
Frontiers in Immunology
○ 638 papers in training set
Top 9%
0.8%
25
Gene
○ 46 papers in training set
Top 2%
0.8%
26
Computers in Biology and Medicine
○ 128 papers in training set
Top 5%
0.8%
27
Computational Biology and Chemistry
○ 28 papers in training set
Top 1%
0.8%
28
Biomolecules
○ 100 papers in training set
Top 4%
0.6%
29
Genes
○ 144 papers in training set
Top 5%
0.6%
30
Virus Research
○ 37 papers in training set
Top 0.9%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.