M. Liang

1.9k total citations · 1 hit paper
7 papers, 94 citations indexed

About

M. Liang is a scholar working on Clinical Biochemistry, Molecular Biology and Management Information Systems. According to data from OpenAlex, M. Liang has authored 7 papers receiving a total of 94 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Clinical Biochemistry, 1 paper in Molecular Biology and 1 paper in Management Information Systems. Recurrent topics in M. Liang's work include Metabolism and Genetic Disorders (2 papers), Aluminum Alloy Microstructure Properties (1 paper) and Semiconductor Quantum Structures and Devices (1 paper). M. Liang is often cited by papers focused on Metabolism and Genetic Disorders (2 papers), Aluminum Alloy Microstructure Properties (1 paper) and Semiconductor Quantum Structures and Devices (1 paper). M. Liang collaborates with scholars based in United States, United Kingdom and China. M. Liang's co-authors include Andreas Schulze, Vanja Sikirica, Ling Jin, Lerong Li, Dwight D. Koeberl, Gerald S. Lipshutz, Stephanie Grünewald, Rajnish Saini, Neal Sondheimer and Tarekegn Geberhiwot and has published in prestigious journals such as Nature, Nature Communications and Renewable Energy.

In The Last Decade

M. Liang

7 papers receiving 90 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.

Interim analyses of a first-in-human phase 1/2 mRNA trial for propionic acidaemia

2024 55 citations Dwight D. Koeberl, Andreas Schulze et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
M. Liang United States	4	64	17	11	10	9	7	94
Vipulkumar Patel United States	5	39 0.6×	16 0.9×		13 1.3×	4 0.4×	8	115
J. Tang China	1	42 0.7×	6 0.4×		7 0.7×	7 0.8×	2	55
Michel Zamojski United States	9	91 1.4×	13 0.8×		10 1.0×	3 0.3×	15	233
C Hughes United Kingdom	4	51 0.8×	21 1.2×	2 0.2×		11 1.2×	5	116
Kelly Shaffer United States	5	100 1.6×	26 1.5×	14 1.3×		2 0.2×	7	140
Rodrigo Bonazzola United States	5	71 1.1×	73 4.3×	3 0.3×		6 0.7×	8	115
Jorge Álvarez-Jarreta Spain	5	64 1.0×	16 0.9×	8 0.7×		3 0.3×	9	99
Abhimanyu Banerjee United States	5	129 2.0×	13 0.8×		2 0.2×	9 1.0×	5	143
S. Kamei Japan	4	36 0.6×	2 0.1×	2 0.2×	13 1.3×		4	89
T. Eifert Switzerland	3	35 0.5×	4 0.2×	3 0.3×	18 1.8×		5	62

Countries citing papers authored by M. Liang

Since Specialization

Citations

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

Fields of papers citing papers by M. Liang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Liang

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Liang, M., et al.. (2025). EnergyGPT: Fine-tuning large language model for multi-energy load forecasting. Renewable Energy. 251. 123313–123313. 2 indexed citations

2.

Baek, Rena, Kimberly A. Coughlan, Lei Jiang, et al.. (2024). Characterizing the mechanism of action for mRNA therapeutics for the treatment of propionic acidemia, methylmalonic acidemia, and phenylketonuria. Nature Communications. 15(1). 3804–3804. 21 indexed citations

3.

Koeberl, Dwight D., Andreas Schulze, Neal Sondheimer, et al.. (2024). Interim analyses of a first-in-human phase 1/2 mRNA trial for propionic acidaemia. Nature. 628(8009). 872–877. 55 indexed citations breakdown →

4.

Liang, M., et al.. (2008). Microscopic phase-field study on atomic site occupation probability in L12–Ni3(Al1−xFex) structure. Materials Letters. 62(28). 4332–4335. 1 indexed citations

5.

Branford, D., A. W. Rauf, J. Lác, et al.. (2000). Electron- and photon-induced proton knockout from209Bi. Physical Review C. 63(1). 10 indexed citations

6.

Liang, M., G. G. Siu, & K. Chan. (1994). A resonant-tunnelling electron wavesplitter. Journal of Physics D Applied Physics. 27(7). 1513–1517. 1 indexed citations

7.

Backer, Stanley, Emery I. Valko, & M. Liang. (1967). The Problems of Textile Information Retrieval1. Textile Research Journal. 37(10). 880–894. 4 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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