Daniel M. Lachance

786 total citations
9 papers, 564 citations indexed

About

Daniel M. Lachance is a scholar working on Molecular Biology, Pharmacology and Physiology. According to data from OpenAlex, Daniel M. Lachance has authored 9 papers receiving a total of 564 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 2 papers in Pharmacology and 2 papers in Physiology. Recurrent topics in Daniel M. Lachance's work include Gut microbiota and health (3 papers), Gastrointestinal motility and disorders (2 papers) and Microbial Natural Products and Biosynthesis (2 papers). Daniel M. Lachance is often cited by papers focused on Gut microbiota and health (3 papers), Gastrointestinal motility and disorders (2 papers) and Microbial Natural Products and Biosynthesis (2 papers). Daniel M. Lachance collaborates with scholars based in United States, Egypt and China. Daniel M. Lachance's co-authors include Mattheos Koffas, J. Andrew Jones, Shannon M. Collins, Mohammad H.A. Ibrahim, Juergen Hahn, Andrew Sinkoe, Neelendu Dey, Li Fu, Victor Schultz and Robert J. Linhardt and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Daniel M. Lachance

9 papers receiving 561 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel M. Lachance United States	8	462	107	99	96	40	9	564
Namita Bhan United States	12	742 1.6×	146 1.4×	128 1.3×	136 1.4×	66 1.6×	13	841
Jiwei Mao China	15	396 0.9×	52 0.5×	93 0.9×	113 1.2×	9 0.2×	27	512
Yunbin Lyu China	15	488 1.1×	128 1.2×	123 1.2×	65 0.7×	10 0.3×	32	613
Haruyuki Yamashita Japan	12	214 0.5×	72 0.7×	52 0.5×	54 0.6×	10 0.3×	17	428
Anna Kujumdzieva Bulgaria	12	253 0.5×	60 0.6×	103 1.0×	33 0.3×	13 0.3×	36	429
Mohammad Kalim Ahmad Khan India	13	193 0.4×	52 0.5×	22 0.2×	40 0.4×	14 0.3×	45	455
Subarna Pokhrel India	8	110 0.2×	34 0.3×	50 0.5×	45 0.5×	10 0.3×	17	290
Sung‐Kwon Lee South Korea	10	184 0.4×	119 1.1×	39 0.4×	21 0.2×	10 0.3×	27	330
Shridhar Patil India	12	287 0.6×	40 0.4×	220 2.2×	45 0.5×	4 0.1×	19	479

Countries citing papers authored by Daniel M. Lachance

Since Specialization

Citations

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

Fields of papers citing papers by Daniel M. Lachance

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel M. Lachance

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Lachance. A scholar is included among the top collaborators of Daniel M. Lachance 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 Daniel M. Lachance. Daniel M. Lachance 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

Orouskhani, Maysam, et al.. (2025). Deep learning imaging analysis to identify bacterial metabolic states associated with carcinogen production. PubMed. 2(1). 2–2. 11 indexed citations

Kamp, Kimberly, Na Li, Daniel M. Lachance, et al.. (2022). Interpersonal Variability in Gut Microbial Calprotectin Metabolism. SHILAP Revista de lepidopterología. 1(5). 853–856. 3 indexed citations

Lachance, Daniel M., et al.. (2021). Variability in digestive and respiratory tract Ace2 expression is associated with the microbiome. PLoS ONE. 16(3). e0248730–e0248730. 31 indexed citations

Lachance, Daniel M., et al.. (2021). Microbiome-encoded bile acid metabolism modulates colonic transit times. iScience. 24(6). 102508–102508. 28 indexed citations

Lachance, Daniel M., et al.. (2021). Marker-based assays for studying gut transit in gnotobiotic and conventional mouse models. STAR Protocols. 2(4). 100938–100938. 9 indexed citations

Jones, J. Andrew, Andrew Sinkoe, Shannon M. Collins, et al.. (2016). Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids. Metabolic Engineering. 35. 55–63. 198 indexed citations

Jones, J. Andrew, Daniel M. Lachance, Li Fu, et al.. (2015). ePathOptimize: A Combinatorial Approach for Transcriptional Balancing of Metabolic Pathways. Scientific Reports. 5(1). 11301–11301. 129 indexed citations

Jones, J. Andrew, et al.. (2015). Optimization of naringenin and p ‐coumaric acid hydroxylation using the native E. coli hydroxylase complex, HpaBC. Biotechnology Progress. 32(1). 21–25. 57 indexed citations

Zhao, Shujuan, J. Andrew Jones, Daniel M. Lachance, et al.. (2014). Improvement of catechin production in Escherichia coli through combinatorial metabolic engineering. Metabolic Engineering. 28. 43–53. 98 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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