Amanda C. Schierz

17 total papers · 1.1k total citations
11 papers, 733 citations indexed

About

Amanda C. Schierz is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Amanda C. Schierz has authored 11 papers receiving a total of 733 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 5 papers in Computational Theory and Mathematics and 4 papers in Artificial Intelligence. Recurrent topics in Amanda C. Schierz's work include Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (4 papers) and Imbalanced Data Classification Techniques (2 papers). Amanda C. Schierz is often cited by papers focused on Bioinformatics and Genomic Networks (5 papers), Computational Drug Discovery Methods (4 papers) and Imbalanced Data Classification Techniques (2 papers). Amanda C. Schierz collaborates with scholars based in United Kingdom. Amanda C. Schierz's co-authors include Bissan Al‐Lazikani, Laurence H. Pearl, Simon E. Ward, Frances M. G. Pearl, Dong Tong, Joseph E Tym, Elizabeth A. Coker, Costas Mitsopoulos, Albert A. Antolín and Krishna C. Bulusu and has published in prestigious journals such as Nucleic Acids Research, Nature reviews. Cancer and Nature Biotechnology.

In The Last Decade

Amanda C. Schierz

11 papers receiving 716 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Amanda C. Schierz	528	195	141	125	56	11	733
Aparna Gorthi	543 1.0×	145 0.7×	96 0.7×	128 1.0×	32 0.6×	23	749
Antonis D. Koutsoukos	411 0.8×	224 1.1×	127 0.9×	83 0.7×	30 0.5×	10	798
Jesse Paquette	351 0.7×	111 0.6×	62 0.4×	148 1.2×	58 1.0×	13	718
Harikrishna Paik	447 0.8×	144 0.7×	131 0.9×	171 1.4×	45 0.8×	37	777
In Sock Jang	518 1.0×	149 0.8×	140 1.0×	143 1.1×	24 0.4×	20	650
Brent M. Kuenzi	508 1.0×	324 1.7×	183 1.3×	107 0.9×	45 0.8×	22	901
Ratna R. Thangudu	586 1.1×	87 0.4×	93 0.7×	136 1.1×	39 0.7×	15	790
Madhu Lal‐Nag	389 0.7×	166 0.9×	69 0.5×	145 1.2×	25 0.4×	19	770
Alina Malyutina	540 1.0×	132 0.7×	226 1.6×	77 0.6×	18 0.3×	12	811
Minjae Yoo	321 0.6×	105 0.5×	96 0.7×	95 0.8×	24 0.4×	14	626

Countries citing papers authored by Amanda C. Schierz

Since Specialization

Citations

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

Fields of papers citing papers by Amanda C. Schierz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amanda C. Schierz. 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 Amanda C. Schierz. The network helps show where Amanda C. Schierz may publish in the future.

Co-authorship network of co-authors of Amanda C. Schierz

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

All Works

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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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