Bertil Schmidt

6.6k total citations
198 papers, 4.0k citations indexed

About

Bertil Schmidt is a scholar working on Molecular Biology, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Bertil Schmidt has authored 198 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 143 papers in Molecular Biology, 92 papers in Artificial Intelligence and 58 papers in Computer Networks and Communications. Recurrent topics in Bertil Schmidt's work include Genomics and Phylogenetic Studies (112 papers), Algorithms and Data Compression (81 papers) and Advanced Data Storage Technologies (32 papers). Bertil Schmidt is often cited by papers focused on Genomics and Phylogenetic Studies (112 papers), Algorithms and Data Compression (81 papers) and Advanced Data Storage Technologies (32 papers). Bertil Schmidt collaborates with scholars based in Germany, Singapore and China. Bertil Schmidt's co-authors include Yongchao Liu, Douglas L. Maskell, Weiguo Liu, Wolfgang Müller‐Wittig, Andreas Hildebrandt, Jan Schröder, Adrianto Wirawan, Jorge González‐Domínguez, Gerrit Voß and Christian Hundt and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Bertil Schmidt

189 papers receiving 3.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bertil Schmidt Germany 34 2.7k 1.6k 720 507 376 198 4.0k
Jeremy Buhler United States 23 3.1k 1.1× 748 0.5× 284 0.4× 230 0.5× 248 0.7× 84 4.2k
Nagiza F. Samatova United States 29 1.3k 0.5× 761 0.5× 820 1.1× 273 0.5× 120 0.3× 142 3.4k
Esko Ukkonen Finland 30 3.8k 1.4× 2.2k 1.4× 366 0.5× 526 1.0× 378 1.0× 117 6.0k
Gene Myers United States 21 1.4k 0.5× 1.4k 0.9× 208 0.3× 420 0.8× 198 0.5× 38 3.0k
Martı́n Farach-Colton United States 33 1.2k 0.4× 2.2k 1.4× 1.5k 2.1× 782 1.5× 200 0.5× 137 4.1k
Kaizhong Zhang Canada 35 2.2k 0.8× 1.5k 0.9× 661 0.9× 104 0.2× 145 0.4× 126 5.4k
Bud Mishra United States 30 1.2k 0.4× 325 0.2× 292 0.4× 130 0.3× 229 0.6× 171 3.0k
Volker Röth Switzerland 36 1.1k 0.4× 1.2k 0.8× 446 0.6× 71 0.1× 139 0.4× 133 4.4k
Robert Giegerich Germany 33 4.3k 1.6× 650 0.4× 123 0.2× 166 0.3× 642 1.7× 113 5.7k
Lusheng Wang Hong Kong 30 1.8k 0.7× 919 0.6× 1.1k 1.6× 56 0.1× 211 0.6× 203 4.4k

Countries citing papers authored by Bertil Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Bertil Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bertil Schmidt. 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 Bertil Schmidt. The network helps show where Bertil Schmidt may publish in the future.

Co-authorship network of co-authors of Bertil Schmidt

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

All Works

20 of 20 papers shown
1.
Schmidt, Bertil, et al.. (2025). Improved vapor pressure predictions using group contribution-assisted graph convolutional neural networks (GC 2 NN). Geoscientific model development. 18(20). 7357–7371.
2.
Zhang, Tong, et al.. (2025). RabbitSketch: a high-performance sketching library for genome analysis. Bioinformatics. 41(5).
3.
Liu, Weiguo, et al.. (2025). HPC and AI in bioinformatics. Future Generation Computer Systems. 174. 108019–108019.
4.
Schmidt, Bertil, et al.. (2024). CUDASW++4.0: ultra-fast GPU-based Smith–Waterman protein sequence database search. BMC Bioinformatics. 25(1). 342–342. 6 indexed citations
5.
Zhang, Tong, et al.. (2024). SWQC: Efficient sequencing data quality control on the next-generation sunway platform. Future Generation Computer Systems. 164. 107577–107577. 2 indexed citations
6.
Xiao-ming, XU, et al.. (2023). RabbitKSSD: accelerating genome distance estimation on modern multi-core architectures. Bioinformatics. 39(11). 3 indexed citations
7.
Gómez-Zepeda, David, et al.. (2022). Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data. BMC Bioinformatics. 23(1). 287–287. 1 indexed citations
8.
Lopes, Nuno, et al.. (2020). Big Data in metagenomics: Apache Spark vs MPI. PLoS ONE. 15(10). e0239741–e0239741. 12 indexed citations
9.
Ringe, Kristina I., Frank Wacker, Henrike Lenzen, et al.. (2020). Fully automated detection of primary sclerosing cholangitis (PSC)-compatible bile duct changes based on 3D magnetic resonance cholangiopancreatography using machine learning. European Radiology. 31(4). 2482–2489. 11 indexed citations
10.
Gutberlet, Marcel, Christian Hundt, Till F. Kaireit, et al.. (2019). Deep semantic lung segmentation for tracking potential pulmonary perfusion biomarkers in chronic obstructive pulmonary disease (COPD): The multi‐ethnic study of atherosclerosis COPD study. Journal of Magnetic Resonance Imaging. 51(2). 571–579. 19 indexed citations
11.
Lan, Haidong, et al.. (2018). MyPhi: Efficient Levenshtein Distance Computation on Xeon Phi Based Architectures. Current Bioinformatics. 13(5). 479–486. 1 indexed citations
12.
Wei, Xiaona, et al.. (2015). A computational method for studying the relation between alternative splicing and DNA methylation. Nucleic Acids Research. 44(2). e19–e19. 11 indexed citations
13.
Aluru, Srinivas, Sanghamitra Bandyopadhyay, Ümit V. Çatalyürek, et al.. (2011). Contemporary Computing: 4th International Conference, IC3 2011, Noida, India, August 8-10, 2011. Proceedings. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1 indexed citations
14.
Rajapakse, Jagath C., et al.. (2007). Pattern recognition in bioinformatics : Second IAPR International Workshop, PRIB 2007, Singapore, October 1-2, 2007 : proceedings. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1 indexed citations
15.
Liu, Weiguo, et al.. (2006). Bio-sequence database scanning on a GPU. International Parallel and Distributed Processing Symposium. 251–251. 64 indexed citations
16.
Schmidt, Bertil, et al.. (2005). Hyper customized processors for bio-sequence database scanning on FPGAs. 229–237. 73 indexed citations
17.
Schimmler, Manfred, et al.. (2003). An Area-Efficient Bit-Serial Integer Multiplier.. IEEE Transactions on Very Large Scale Integration (VLSI) Systems. 131–137.
18.
Schmidt, Bertil, et al.. (2003). Computing Large-scale Alignments on a Multi-cluster. Cluster Computing. 38–45. 14 indexed citations
19.
Schmidt, Bertil, Heiko Schröder, & Manfred Schimmler. (2001). Tomographic image reconstruction on the instruction systolic array. Computing and Informatics / Computers and Artificial Intelligence. 20(1). 27–42. 1 indexed citations
20.
Schmidt, Bertil & Manfred Schimmler. (2000). KPROC—An Instruction Systolic Architecture for Parallel Prefix Applications. Scalable Computing Practice and Experience. 3(2). 1 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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