Mahnaz Abbasian

900 total citations · 1 hit paper
6 papers, 403 citations indexed

About

Mahnaz Abbasian is a scholar working on Molecular Biology, Infectious Diseases and Surgery. According to data from OpenAlex, Mahnaz Abbasian has authored 6 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 2 papers in Infectious Diseases and 1 paper in Surgery. Recurrent topics in Mahnaz Abbasian's work include SARS-CoV-2 and COVID-19 Research (2 papers), vaccines and immunoinformatics approaches (1 paper) and Machine Learning in Bioinformatics (1 paper). Mahnaz Abbasian is often cited by papers focused on SARS-CoV-2 and COVID-19 Research (2 papers), vaccines and immunoinformatics approaches (1 paper) and Machine Learning in Bioinformatics (1 paper). Mahnaz Abbasian collaborates with scholars based in United Kingdom, Malaysia and India. Mahnaz Abbasian's co-authors include Clemens Rauer, Christine Orengo, Vaishali Waman, Neeladri Sen, Nicola Bordin, Su Datt Lam, Camilla Pang, Paul Ashford, Natalie L. Dawson and Jonathan Lees and has published in prestigious journals such as Nucleic Acids Research, Scientific Reports and Current Opinion in Structural Biology.

In The Last Decade

Mahnaz Abbasian

6 papers receiving 399 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

CATH: increased structural coverage of functional space

2020 280 citations Ian Sillitoe, Nicola Bordin et al. Nucleic Acids Research profile →

Peers

Mahnaz Abbasian

MB

MC

ID

CTM

ECOLO

Harry Scholes United Kingdom

Camilla Pang United Kingdom

B. Jeevan United States

Stephanie Portelli Australia

Yu-An Kung Taiwan

Amitava Roy United States

G. Kalnins Latvia

Ali H. A. Maghrabi United Kingdom

Chengrong Liu China

Hyeonuk Woo South Korea

Harry Scholes United Kingdom

Mahnaz Abbasian

379 ×1.4

MB

95 ×1.2

MC

86 ×1.1

ID

57 ×1.3

CTM

37 ×1.4

ECOLO

Citations per year, relative to Mahnaz Abbasian Mahnaz Abbasian (= 1×) peers Harry Scholes

Countries citing papers authored by Mahnaz Abbasian

Since Specialization

Citations

This map shows the geographic impact of Mahnaz Abbasian'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 Mahnaz Abbasian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mahnaz Abbasian more than expected).

Fields of papers citing papers by Mahnaz Abbasian

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mahnaz Abbasian. 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 Mahnaz Abbasian. The network helps show where Mahnaz Abbasian may publish in the future.

Co-authorship network of co-authors of Mahnaz Abbasian

This figure shows the co-authorship network connecting the top 25 collaborators of Mahnaz Abbasian. A scholar is included among the top collaborators of Mahnaz Abbasian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mahnaz Abbasian. Mahnaz Abbasian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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6 of 6 papers shown

1.

Waman, Vaishali, Paul Ashford, Su Datt Lam, et al.. (2024). Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics. Scientific Reports. 14(1). 14208–14208. 1 indexed citations

2.

Rauer, Clemens, Neeladri Sen, Vaishali Waman, Mahnaz Abbasian, & Christine Orengo. (2021). Computational approaches to predict protein functional families and functional sites. Current Opinion in Structural Biology. 70. 108–122. 18 indexed citations

3.

Lam, Su Datt, Nicola Bordin, Vaishali Waman, et al.. (2020). SARS-CoV-2 spike protein predicted to form complexes with host receptor protein orthologues from a broad range of mammals. Scientific Reports. 10(1). 16471–16471. 80 indexed citations

4.

Sillitoe, Ian, Nicola Bordin, Natalie L. Dawson, et al.. (2020). CATH: increased structural coverage of functional space. Nucleic Acids Research. 49(D1). D266–D273. 280 indexed citations breakdown →

5.

Goh, Pollyanna, et al.. (2018). Mbd3 Promotes Reprogramming of Primary Human Fibroblasts. International Journal of Stem Cells. 11(2). 235–241. 4 indexed citations

6.

Chachi, Latifa, Mahnaz Abbasian, Abdulrahman Alzahrani, et al.. (2016). Protein phosphatase 5 mediates corticosteroid insensitivity in airway smooth muscle in patients with severe asthma. Allergy. 72(1). 126–136. 20 indexed citations

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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