Daniel B. Larach

23 papers receiving 945 citations

Daniel B. Larach's Hit Papers

Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease 2016 · 469 citations
4690+3+6Years since publication100200300400

Peers

Daniel B. Larach
Comparison fields: 5 of 84
  • Endocrinology, Diabetes and Metabolism 202
  • Anesthesiology and Pain Medicine 47
  • Surgery 315
  • Cancer Research 103
  • Nephrology 48
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S Jambart Lebanon
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Countries citing papers authored by Daniel B. Larach

Since Specialization
Citations

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

Fields of papers citing papers by Daniel B. Larach

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel B. Larach, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel B. Larach Line = papers co-authored together Daniel B. Larach links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease
Hit paper breakdown →
2016469
2 201893
3 201968
4 201954
5 201146
6 201544
7 202244
8 201229
9 200927
10 201720
11 202018
12 201912
13 201610
14 20139
15 20238
16 20236
17 20226
18 20195
19 20233
20 20242

About Daniel B. Larach

Daniel B. Larach is a scholar working on Public Health, Environmental and Occupational Health, Nephrology, Anesthesiology and Pain Medicine, Endocrinology, Diabetes and Metabolism and Surgery, having authored 26 papers that have together received 979 indexed citations. Recurring topics across this work include Opioid Use Disorder Treatment (9 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (3 papers), Pain Management and Opioid Use (3 papers), Genetic Associations and Epidemiology (3 papers), Acute Kidney Injury Research (3 papers), Lipoproteins and Cardiovascular Health (2 papers), Chronic Kidney Disease and Diabetes (2 papers) and Cholesterol and Lipid Metabolism (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (202 citations), Anesthesiology and Pain Medicine (47 citations), Surgery (315 citations), Cancer Research (103 citations) and Nephrology (48 citations). Daniel B. Larach has collaborated with scholars based in United States, Norway and Netherlands. Frequent co-authors include Chad M. Brummet, Jennifer F. Waljee, William Andrew Kofke, Peter Le Roux, Jennifer M. Hah, Michael J. Englesbe, Daniel James Rader, Nalliah Romesh, Hsou-Mei Hu and Jay Soong-Jin Lee. Their work appears in journals such as Annals of Surgery, Regional Anesthesia & Pain Medicine, Pain Medicine, Neurocritical Care and Frontiers in Genetics.

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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