Colin A. Grambow

2.0k total citations · 2 hit papers
15 papers, 1.3k citations indexed

About

Colin A. Grambow is a scholar working on Materials Chemistry, Computational Theory and Mathematics and Molecular Biology. According to data from OpenAlex, Colin A. Grambow has authored 15 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Materials Chemistry, 9 papers in Computational Theory and Mathematics and 5 papers in Molecular Biology. Recurrent topics in Colin A. Grambow's work include Machine Learning in Materials Science (11 papers), Computational Drug Discovery Methods (9 papers) and Protein Structure and Dynamics (4 papers). Colin A. Grambow is often cited by papers focused on Machine Learning in Materials Science (11 papers), Computational Drug Discovery Methods (9 papers) and Protein Structure and Dynamics (4 papers). Colin A. Grambow collaborates with scholars based in United States, Israel and Cyprus. Colin A. Grambow's co-authors include William H. Green, Anne‐Marie Kietzig, K. M. Tanvir Ahmmed, Lagnajit Pattanaik, Yi‐Pei Li, Kehang Han, Gabriele Scalia, Barbara Pernici, Adeel Jamal and Alon Grinberg Dana and has published in prestigious journals such as Journal of the American Chemical Society, Physical Chemistry Chemical Physics and The Journal of Physical Chemistry Letters.

In The Last Decade

Colin A. Grambow

15 papers receiving 1.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Fabrication of Micro/Nano Structures on Metals by Femtosecond Laser Micromachining

2014 347 citations K. M. Tanvir Ahmmed, Colin A. Grambow et al. Micromachines profile →
Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

2021 197 citations Mengjie Liu, Alon Grinberg Dana et al. Journal of Chemical Information and Modeling profile →

Peers

Colin A. Grambow

CTM

AMPO

Richard H. West United States

Jinzhe Zeng United States

Jorge Aguilera‐Iparraguirre United States

Joshua W. Allen United States

Connie W. Gao United States

Richard A. Messerly United States

Bingqing Cheng Austria

Judit Zádor United States

C. Franklin Goldsmith United States

Leif C. Kröger Germany

Richard H. West United States

Colin A. Grambow

1.1k ×1.5

249 ×0.6

CTM

477 ×1.7

400 ×1.7

330 ×1.7

AMPO

Citations per year, relative to Colin A. Grambow Colin A. Grambow (= 1×) peers Richard H. West

Countries citing papers authored by Colin A. Grambow

Since Specialization

Citations

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

Fields of papers citing papers by Colin A. Grambow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Colin A. Grambow. 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 Colin A. Grambow. The network helps show where Colin A. Grambow may publish in the future.

Co-authorship network of co-authors of Colin A. Grambow

This figure shows the co-authorship network connecting the top 25 collaborators of Colin A. Grambow. A scholar is included among the top collaborators of Colin A. Grambow 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 Colin A. Grambow. Colin A. Grambow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

Grambow, Colin A., et al.. (2024). CREMP: Conformer-rotamer ensembles of macrocyclic peptides for machine learning. Scientific Data. 11(1). 859–859. 7 indexed citations

Wu, Haoyang, A. Mark Payne, Hao‐Wei Pang, et al.. (2024). Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions. The Journal of Physical Chemistry A. 128(21). 4335–4352. 7 indexed citations

Johnson, Matthew S., Alon Grinberg Dana, Yunsie Chung, et al.. (2022). RMG Database for Chemical Property Prediction. Journal of Chemical Information and Modeling. 62(20). 4906–4915. 88 indexed citations

Liu, Mengjie, Alon Grinberg Dana, Matthew S. Johnson, et al.. (2021). Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation. Journal of Chemical Information and Modeling. 61(6). 2686–2696. 197 indexed citations breakdown →

Grambow, Colin A., Lagnajit Pattanaik, & William H. Green. (2020). Reactants, products, and transition states of elementary chemical reactions based on quantum chemistry. Scientific Data. 7(1). 137–137. 108 indexed citations

Pattanaik, Lagnajit, John Ingraham, Colin A. Grambow, & William H. Green. (2020). Generating transition states of isomerization reactions with deep learning. Physical Chemistry Chemical Physics. 22(41). 23618–23626. 55 indexed citations

Scalia, Gabriele, Colin A. Grambow, Barbara Pernici, Yi‐Pei Li, & William H. Green. (2020). Evaluating Scalable Uncertainty Estimation Methods for Deep Learning-Based Molecular Property Prediction. Journal of Chemical Information and Modeling. 60(6). 2697–2717. 144 indexed citations

Grambow, Colin A., et al.. (2020). chemprop-reaction: Release version 1.1.0. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

Grambow, Colin A., Lagnajit Pattanaik, & William H. Green. (2020). Deep Learning of Activation Energies. The Journal of Physical Chemistry Letters. 11(8). 2992–2997. 132 indexed citations

10.

Li, Yi‐Pei, Kehang Han, Colin A. Grambow, & William H. Green. (2019). Self-Evolving Machine: A Continuously Improving Model for Molecular Thermochemistry. The Journal of Physical Chemistry A. 123(10). 2142–2152. 47 indexed citations

11.

Grambow, Colin A.. (2019). cgrambow/ard_gsm: Release version 1.0.0. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations

12.

Grambow, Colin A., Yi‐Pei Li, & William H. Green. (2019). Accurate Thermochemistry with Small Data Sets: A Bond Additivity Correction and Transfer Learning Approach. The Journal of Physical Chemistry A. 123(27). 5826–5835. 84 indexed citations

13.

Han, Kehang, Adeel Jamal, Colin A. Grambow, Zachary J. Buras, & William H. Green. (2018). An Extended Group Additivity Method for Polycyclic Thermochemistry Estimation. International Journal of Chemical Kinetics. 50(4). 294–303. 32 indexed citations

14.

Grambow, Colin A., Adeel Jamal, Yi‐Pei Li, et al.. (2017). Unimolecular Reaction Pathways of a γ-Ketohydroperoxide from Combined Application of Automated Reaction Discovery Methods. Journal of the American Chemical Society. 140(3). 1035–1048. 87 indexed citations

15.

Ahmmed, K. M. Tanvir, Colin A. Grambow, & Anne‐Marie Kietzig. (2014). Fabrication of Micro/Nano Structures on Metals by Femtosecond Laser Micromachining. Micromachines. 5(4). 1219–1253. 347 indexed citations breakdown →

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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