Hannah Chang
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
- Modeling and Simulation top 2%
Papers in
-
- Gene Regulatory Network Analysis 5
- Single-cell and spatial transcriptomics 3
- Co-authors
- Sui Huang (5 shared papers)Donald E. Ingber (2 shared papers)Mauricio Barahona (1 shared paper)Martin Hemberg (1 shared paper)Amy Brock (1 shared paper)Christopher P. Howson (2 shared papers)Jim Larson (2 shared papers)Catherine Y. Spong (2 shared papers)
- Journals
- The Lancet (2 papers)iScience (1 paper)ACS Sustainable Chemistry & Engineering (1 paper)PLoS Biology (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Hannah Chang
12 papers receiving 2.0k citations
Hannah Chang's Hit Papers
Peers
Comparison fields: 5 of 131
- Biophysics 175
- Modeling and Simulation 120
- Aging 35
- Obstetrics and Gynecology 144
- Molecular Biology 1.2k
Countries citing papers authored by Hannah Chang
This map shows the geographic impact of Hannah Chang'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 Hannah Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hannah Chang more than expected).
Fields of papers citing papers by Hannah Chang
This network shows the impact of papers produced by Hannah Chang. 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 Hannah Chang. The network helps show where Hannah Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside Hannah Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Transcriptome-wide noise controls lineage choice in mammalian progenitor cells Hit paper breakdown → | 2008 | 838 |
| 2 | Preventing preterm births: analysis of trends and potential reductions with interventions in 39 countries with very high human development index Hit paper breakdown → | 2012 | 407 |
| 3 | 2009 | 361 | |
| 4 | 2016 | 223 | |
| 5 | 2012 | 155 | |
| 6 | 2008 | 74 | |
| 7 | 2012 | 9 | |
| 8 | 2011 | 7 | |
| 9 | 2024 | 7 | |
| 10 | 2013 | 1 | |
| 11 | The (behavioral) science behind baby milk formula | 2018 | 1 |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 |
About Hannah Chang
Hannah Chang is a scholar working on Molecular Biology, Social Psychology, Pediatrics, Perinatology and Child Health, Clinical Psychology and Epidemiology, having authored 14 papers that have together received 2.1k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (5 papers), Single-cell and spatial transcriptomics (3 papers), Global Maternal and Child Health (2 papers), Preterm Birth and Chorioamnionitis (2 papers), Animal Genetics and Reproduction (1 paper), Cell Image Analysis Techniques (1 paper), Delphi Technique in Research (1 paper) and Ecosystem dynamics and resilience (1 paper). The work is most often cited by research in Biophysics (175 citations), Modeling and Simulation (120 citations), Aging (35 citations), Obstetrics and Gynecology (144 citations) and Molecular Biology (1.2k citations). Hannah Chang has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Sui Huang, Donald E. Ingber, Mauricio Barahona, Martin Hemberg, Amy Brock, Christopher P. Howson, Jim Larson, Catherine Y. Spong, Joy E Lawn and Joe Leigh Simpson. Their work appears in journals such as The Lancet, iScience, ACS Sustainable Chemistry & Engineering, PLoS Biology and BMC Bioinformatics.
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.