Daniel Peisach
- Cell Biology top 5%
- Endoplasmic Reticulum Stress and Disease 2
- Neurology top 5%
- Amyotrophic Lateral Sclerosis Research 2
- Biochemistry top 5%
- Amino Acid Enzymes and Metabolism 5
- Aging top 10%
- Genetics top 10%
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- Enzyme Structure and Function 9
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- Autophagy in Disease and Therapy 2
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- Chemical Synthesis and Analysis 2
- Polyamine Metabolism and Applications 2
- Biochemical and Molecular Research 2
- Co-authors
- Zhaohui XuJiahai ZhouRandal J. KaufmanChuan Yin LiuRobert L. ClarkSung Hoon BackDagmar RingeSami J. Barmada
- Cited by
- Cell BiologyNeurologyBiochemistry
- Journals
- Biochemistry (4 papers)Protein Science (2 papers)Proceedings of the National Academy of Sciences (2 papers)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Daniel Peisach
15 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 79
- Cell Biology 361
- Neurology 265
- Biochemistry 102
- Aging 19
- Genetics 113
Countries citing papers authored by Daniel Peisach
This map shows the geographic impact of Daniel Peisach'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 Peisach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Peisach more than expected).
Fields of papers citing papers by Daniel Peisach
This network shows the impact of papers produced by Daniel Peisach. 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 Peisach. The network helps show where Daniel Peisach may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Daniel Peisach, 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 | 2019 | 10 | |
| 2 | 2015 | 93 | |
| 3 | Autophagy induction enhances TDP43 turnover and survival in neuronal ALS modelsbreakdown → | 2014 | 341 |
| 4 | 2006 | 285 | |
| 5 | 2005 | 17 | |
| 6 | 2004 | 35 | |
| 7 | 2003 | 59 | |
| 8 | 1999 | 14 | |
| 9 | 1998 | 12 | |
| 10 | 1998 | 42 | |
| 11 | 1998 | 70 | |
| 12 | 1997 | 119 | |
| 13 | 1995 | 5 | |
| 14 | 1993 | 35 | |
| 15 | 1993 | 52 |
About Daniel Peisach
Daniel Peisach is a scholar working on Biochemistry, Physiology, Materials Chemistry, Clinical Biochemistry and Neurology, having authored 15 papers that have together received 1.2k indexed citations. Recurring topics across this work include Enzyme Structure and Function (9 papers), Amino Acid Enzymes and Metabolism (5 papers), Autophagy in Disease and Therapy (2 papers), Chemical Synthesis and Analysis (2 papers), Amyotrophic Lateral Sclerosis Research (2 papers), Polyamine Metabolism and Applications (2 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Biochemical and Molecular Research (2 papers). The work is most often cited by research in Cell Biology (361 citations), Neurology (265 citations), Biochemistry (102 citations), Aging (19 citations) and Genetics (113 citations). Daniel Peisach has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include Zhaohui Xu, Jiahai Zhou, Randal J. Kaufman, Chuan Yin Liu, Robert L. Clark, Sung Hoon Back, Dagmar Ringe, Sami J. Barmada, Arpana Arjun and Steven Finkbeiner. Their work appears in journals such as Biochemistry, Protein Science, Proceedings of the National Academy of Sciences, Protein Engineering Design and Selection and Journal of the American Chemical Society.
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.