Mohammadamin Edrisi

743 total citations · 1 hit paper
9 papers, 350 citations indexed

About

Mohammadamin Edrisi is a scholar working on Molecular Biology, Cancer Research and Artificial Intelligence. According to data from OpenAlex, Mohammadamin Edrisi has authored 9 papers receiving a total of 350 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Cancer Research and 2 papers in Artificial Intelligence. Recurrent topics in Mohammadamin Edrisi's work include Cancer Genomics and Diagnostics (6 papers), Single-cell and spatial transcriptomics (6 papers) and Genomic variations and chromosomal abnormalities (2 papers). Mohammadamin Edrisi is often cited by papers focused on Cancer Genomics and Diagnostics (6 papers), Single-cell and spatial transcriptomics (6 papers) and Genomic variations and chromosomal abnormalities (2 papers). Mohammadamin Edrisi collaborates with scholars based in United States, Australia and India. Mohammadamin Edrisi's co-authors include Luay Nakhleh, Nicholas E. Navin, Xian Mallory, CJ Barberan, Advait Balaji, Chen Dun, Todd J. Treangen, Richard G. Baraniuk, Nicolae Sapoval and Ruth Dannenfelser and has published in prestigious journals such as Nature Communications, Bioinformatics and Genome biology.

In The Last Decade

Mohammadamin Edrisi

8 papers receiving 339 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.

Current progress and open challenges for applying deep learning across the biosciences

2022 171 citations Nicolae Sapoval, Amirali Aghazadeh et al. Nature Communications profile →

Peers

Countries citing papers authored by Mohammadamin Edrisi

Since Specialization

Citations

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

Fields of papers citing papers by Mohammadamin Edrisi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammadamin Edrisi

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammadamin Edrisi. A scholar is included among the top collaborators of Mohammadamin Edrisi 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 Mohammadamin Edrisi. Mohammadamin Edrisi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

#	Work	Indexed citations
1	NestedBD: Bayesian inference of phylogenetic trees from single-cell copy number profiles under a birth-death model 2024 ·Algorithms for Molecular Biology ·Yushu Liu, Mohammadamin Edrisi, Zhi Yan, Huw A. Ogilvie, Luay Nakhleh	3
2	Accurate integration of single-cell DNA and RNA for analyzing intratumor heterogeneity using MaCroDNA 2023 ·Nature Communications ·Mohammadamin Edrisi, (unknown), Huw A. Ogilvie, Luay Nakhleh	8
3	Current progress and open challenges for applying deep learning across the biosciences breakdown → 2022 ·Nature Communications ·Nicolae Sapoval, Amirali Aghazadeh, Michael Nute, Dinler A. Antunes, Advait Balaji, Richard G. Baraniuk, CJ Barberan, Ruth Dannenfelser, Chen Dun, Mohammadamin Edrisi, R. A. Leo Elworth, Bryce Kille, Anastasios Kyrillidis, Luay Nakhleh, C. Wolfe, Zhi Yan, Vicky Yao, Todd J. Treangen	171
4	Phylovar: toward scalable phylogeny-aware inference of single-nucleotide variations from single-cell DNA sequencing data 2022 ·Bioinformatics ·Mohammadamin Edrisi, (unknown), (unknown), (unknown), Huw A. Ogilvie, David Posada, Hamim Zafar, Luay Nakhleh	5
5	Assessing the performance of methods for copy number aberration detection from single-cell DNA sequencing data 2020 ·PLoS Computational Biology ·Xian Mallory, Mohammadamin Edrisi, Nicholas E. Navin, Luay Nakhleh	26
6	Methods for copy number aberration detection from single-cell DNA-sequencing data 2020 ·Genome biology ·Xian Mallory, Mohammadamin Edrisi, Nicholas E. Navin, Luay Nakhleh	84
7	Towards Cognitive Recommender Systems 2020 ·Algorithms ·Amin Beheshti, Shahpar Yakhchi, (unknown), Seyed Mohssen Ghafari, (unknown), Mohammadamin Edrisi	49
8	A Combinatorial Approach for Single-cell Variant Detection via Phylogenetic Inference 2019 ·DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) ·Mohammadamin Edrisi, Hamim Zafar, Luay Nakhleh	0
9	Meta-aligner: long-read alignment based on genome statistics 2017 ·BMC Bioinformatics ·(unknown), (unknown), (unknown), Mohammadamin Edrisi, Seyed Abolfazl Motahari, Babak Hossein Khalaj	4

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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