ResearcherJohns Hopkins UniversityActive in the last 2 years
Ashley L. Kiemen
Matched on ORCID iD 0000-0002-6281-2616; OpenAlex author ID A5023048313, A5126300625. Sources: OpenAlex.
Their work
- Papers
- 10
- Trials
- 0
- Grants
- 1
- Labs led
- 0
- Collaborators
- 64
2022: 1 paper · 2023: 2 papers, 1 grant · 2024: 2 papers · 2025: 1 paper · 2026: 4 papers
Papers 10
- Pancreatic ductal adenocarcinoma: The Vision of Heracles. Co-author DOI 10.1016/j.ccell.2026.07.014↗
- Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. Co-author DOI 10.1016/j.cpblue.2026.100008↗
- Cancer interception with KRAS inhibitors in preclinical models of pancreatic ductal adenocarcinoma. Co-author DOI 10.1126/science.aec7929↗
- Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer Co-author DOI 10.64898/2026.03.03.709150↗
- Myc and Kras cooperate in adult acinar cells to drive phenotypic heterogeneity, metastasis, and therapeutic resistance in a novel pancreatic cancer mouse model Co-author DOI 10.1101/2025.07.14.664767↗
- Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancreatic cancer immunotherapy pathologic resp… Co-author DOI 10.1101/2024.09.22.613714↗
- Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings. Co-author DOI 10.1126/sciadv.ado5103↗
- Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic cancer. Co-author DOI 10.1016/j.medj.2022.11.009↗
- Intraparenchymal metastases as a cause for local recurrence of pancreatic cancer. Co-author DOI 10.1111/his.14839↗
- CODA: quantitative 3D reconstruction of large tissues at cellular resolution Co-author DOI 10.1038/s41592-022-01650-9↗
Grants 1
Closest collaborators
The 25 strongest of 64 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Laura DeLong Wood · 8 shared papers, 2022–2026 · strength 1.50
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic… DOI 10.1126/sciadv.ado5103↗
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Denis Wirtz · 6 shared papers, 2022–2026 · strength 1.14
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic… DOI 10.1126/sciadv.ado5103↗
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Ralph H. Hruban · 5 shared papers, 2022–2026 · strength 0.91
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic… DOI 10.1126/sciadv.ado5103↗
- Paper Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic ca… DOI 10.1016/j.medj.2022.11.009↗
- Won Jin Ho · 3 shared papers, 2024–2026 · strength 0.60
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Paper Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancrea… DOI 10.1101/2024.09.22.613714↗
- Toby C. Cornish · 3 shared papers, 2022–2026 · strength 0.58
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic… DOI 10.1126/sciadv.ado5103↗
- Paper CODA: quantitative 3D reconstruction of large tissues at cellular resolution DOI 10.1038/s41592-022-01650-9↗
- Pei-Hsun Wu · 3 shared papers, 2022–2026 · strength 0.57
- Paper Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic… DOI 10.1126/sciadv.ado5103↗
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Paper CODA: quantitative 3D reconstruction of large tissues at cellular resolution DOI 10.1038/s41592-022-01650-9↗
- Pei-Hsun wu · 3 shared papers, 2023–2026 · strength 0.56
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Tissue clearing and 3D reconstruction of digitized, serially sectioned slides provide novel insights into pancreatic ca… DOI 10.1016/j.medj.2022.11.009↗
- Paper Intraparenchymal metastases as a cause for local recurrence of pancreatic cancer. DOI 10.1111/his.14839↗
- André Forjaz · 2 shared papers, 2026 · strength 0.46
- Paper Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression. DOI 10.1016/j.cpblue.2026.100008↗
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Dimitrios N. Sidiropoulos · 2 shared papers, 2024–2026 · strength 0.37
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Paper Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancrea… DOI 10.1101/2024.09.22.613714↗
- Elana Judith Fertig · 2 shared papers, 2024–2026 · strength 0.37
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Paper Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancrea… DOI 10.1101/2024.09.22.613714↗
- Luciane Tsukamoto Kagohara · 2 shared papers, 2024–2026 · strength 0.37
- Paper Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in … DOI 10.64898/2026.03.03.709150↗
- Paper Spatial multi-omics reveal intratumoral humoral immunity niches associated with tertiary lymphoid structures in pancrea… DOI 10.1101/2024.09.22.613714↗
- A. Cole Edwards · 1 shared paper, 2026 · strength 0.23
- Minh T. Than · 1 shared paper, 2026 · strength 0.23
- Ben Z. Stanger · 1 shared paper, 2026 · strength 0.23
- Robert H. Vonderheide · 1 shared paper, 2026 · strength 0.23
- David Zwicker · 1 shared paper, 2024 · strength 0.23
- Paola A. Guerrero · 1 shared paper, 2026 · strength 0.22
- Vincent Bernard Pagan · 1 shared paper, 2026 · strength 0.22
- Pilhan Kim · 1 shared paper, 2026 · strength 0.19
- Marina Lesina · 1 shared paper, 2026 · strength 0.19
- Chiara Falcomatà · 1 shared paper, 2026 · strength 0.19
- Marie C. Hasselluhn · 1 shared paper, 2026 · strength 0.19
- Kıvanç Görgülü · 1 shared paper, 2026 · strength 0.19
- Didem Karakaş · 1 shared paper, 2026 · strength 0.19
- Yetiş Gültekin · 1 shared paper, 2026 · strength 0.19
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.