Bilal Shaker

1.2k citations
21 papers · 771 · 1 hit paper · h-index 12

Impact in

Papers in

Bilal Shaker

20 papers receiving 762 citations

Hit Papers

In silico methods and tools for drug discovery 2021 · 352 citations
3520+1+3Years since publication100200300

Peers

Bilal Shaker
Comparison fields: 5 of 112
  • Computational Theory and Mathematics 276
  • Virology 35
  • Molecular Medicine 32
  • Molecular Biology 426
  • Drug Discovery 1
Replace Utkarsh Raj with:
Utkarsh Raj India
Shailima Rampogu South Korea
Shopnil Akash Bangladesh
Eduardo Habib Bechelane Maia Brazil
Chetna Tyagi India
Wenqiang Cui China
Foysal Ahammad Saudi Arabia
Sako Mirzaie Iran
Prasenjit Bhaumik India
Bilal Shaker relative to Utkarsh Raj India Utkarsh Raj's profile →
Citations per field
00.5×3.2×
Utkarsh Raj · 1×
Citations per year

Countries citing papers authored by Bilal Shaker

Since Specialization
Citations

This map shows the geographic impact of Bilal Shaker's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bilal Shaker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bilal Shaker more than expected).

Fields of papers citing papers by Bilal Shaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bilal Shaker. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bilal Shaker. The network helps show where Bilal Shaker may publish in the future.

Co-authors

The 25 scholars most cited alongside Bilal Shaker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bilal Shaker Line = papers co-authored together Bilal Shaker links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
In silico methods and tools for drug discovery
Hit paper breakdown →
2021352
2 2020121
3 202241
4 202240
5 202037
6 202326
7 202224
8 202123
9 202021
10 202215
11 202013
12 201811
13 202210
14 202010
15 20248
16 20226
17 20255
18 20233
19 20233
20 20242

About Bilal Shaker

Bilal Shaker is a scholar working on Molecular Biology, Computational Theory and Mathematics, Molecular Medicine, Infectious Diseases and Pharmacology, having authored 21 papers that have together received 771 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (8 papers), vaccines and immunoinformatics approaches (7 papers), Antibiotic Resistance in Bacteria (3 papers), Machine Learning in Bioinformatics (2 papers), Microbial Natural Products and Biosynthesis (2 papers), Bacteriophages and microbial interactions (2 papers), Genetics and Neurodevelopmental Disorders (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Computational Theory and Mathematics (276 citations), Virology (35 citations), Molecular Medicine (32 citations), Molecular Biology (426 citations) and Drug Discovery (1 citation). Bilal Shaker has collaborated with scholars based in South Korea, Pakistan and Saudi Arabia. Frequent co-authors include Dokyun Na, Sajjad Ahmad, Jingyu Lee, Kwang‐Seok Oh, Myeong‐Sang Yu, Sunjoo Ahn, Jin Sook Song, Jae Yong Ryu, Muhammad Tahir ul Qamar and Saba Ismail. Their work appears in journals such as Bioinformatics, Computers in Biology and Medicine, Vaccines, Journal of Biomolecular Structure and Dynamics and Frontiers in Immunology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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