Heike Sichtig

1.1k total citations
11 papers, 653 citations indexed

About

Heike Sichtig is a scholar working on Artificial Intelligence, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Heike Sichtig has authored 11 papers receiving a total of 653 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Molecular Biology and 3 papers in Cognitive Neuroscience. Recurrent topics in Heike Sichtig's work include Evolutionary Algorithms and Applications (3 papers), Neural dynamics and brain function (3 papers) and Neural Networks and Reservoir Computing (3 papers). Heike Sichtig is often cited by papers focused on Evolutionary Algorithms and Applications (3 papers), Neural dynamics and brain function (3 papers) and Neural Networks and Reservoir Computing (3 papers). Heike Sichtig collaborates with scholars based in United States and Finland. Heike Sichtig's co-authors include Nathan A. Ledeboer, Chelsie N. Geyer, Brittany Goldberg, George M. Weinstock, Luke J. Tallon, Christopher E. Mason, Daniela Bezdan, Alexa B. R. McIntyre, Noah Alexander and Kirill Grigorev and has published in prestigious journals such as Nature Communications, PLoS ONE and Journal of Neurophysiology.

In The Last Decade

Heike Sichtig

10 papers receiving 646 citations

Peers

Heike Sichtig

MB

EPIDE

ID

CB

ECOLO

Lisa Sadzewicz United States

Mihail Halachev United Kingdom

Kirill Kryukov Japan

Christopher P. Stefan United States

Zhuang Wang China

G. J. Hageage United States

Eneida Hatcher United States

Adrienne T. Hall United States

Wilson W. Ng Hong Kong

Gloria León-Ávila Mexico

Lisa Sadzewicz United States

Heike Sichtig

254 ×0.9

MB

102 ×0.7

EPIDE

113 ×1.1

ID

24 ×0.3

CB

78 ×1.1

ECOLO

Citations per year, relative to Heike Sichtig Heike Sichtig (= 1×) peers Lisa Sadzewicz

Countries citing papers authored by Heike Sichtig

Since Specialization

Citations

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

Fields of papers citing papers by Heike Sichtig

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heike Sichtig

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

All Works

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11 of 11 papers shown

1.

Sichtig, Heike, Timothy D. Minogue, Yi Yan, et al.. (2019). FDA-ARGOS is a database with public quality-controlled reference genomes for diagnostic use and regulatory science. Nature Communications. 10(1). 3313–3313. 261 indexed citations

2.

McIntyre, Alexa B. R., Noah Alexander, Kirill Grigorev, et al.. (2019). Single-molecule sequencing detection of N6-methyladenine in microbial reference materials. Nature Communications. 10(1). 579–579. 113 indexed citations

3.

Verratti, Kathleen, et al.. (2018). Extra-Chromosomal DNA Sequencing Reveals Episomal Prophages Capable of Impacting Virulence Factor Expression in Staphylococcus aureus. Frontiers in Microbiology. 9. 1406–1406. 18 indexed citations

4.

Goldberg, Brittany, Heike Sichtig, Chelsie N. Geyer, Nathan A. Ledeboer, & George M. Weinstock. (2015). Making the Leap from Research Laboratory to Clinic: Challenges and Opportunities for Next-Generation Sequencing in Infectious Disease Diagnostics. mBio. 6(6). e01888–15. 240 indexed citations

5.

Nazarian, Alireza, Heike Sichtig, & Alberto Riva. (2012). A Knowledge-Based Method for Association Studies on Complex Diseases. PLoS ONE. 7(9). e44162–e44162. 1 indexed citations

6.

Sichtig, Heike, J. David Schaffer, & Alberto Riva. (2010). Evolving Spiking Neural Networks for predicting transcription factor binding sites. 5. 1–8.

7.

Rosen, Andrew M., Heike Sichtig, J. David Schaffer, & Patricia M. Di Lorenzo. (2010). Taste-Specific Cell Assemblies in a Biologically Informed Model of the Nucleus of the Solitary Tract. Journal of Neurophysiology. 104(1). 4–17. 5 indexed citations

8.

Sichtig, Heike, et al.. (2009). The sge framework: discovering spatio-temporal patterns in biological systems with spiking neural networks(s), a genetic algorithm(g) and expert knowledge(e). 6 indexed citations

9.

Schaffer, J. David, et al.. (2009). A series of failed and partially successful fitness functions for evolving spiking neural networks. 2661–2664. 5 indexed citations

10.

Sichtig, Heike, et al.. (2008). SSNNS -. 1787–1790. 2 indexed citations

11.

Sichtig, Heike. (2007). Building Smart Machines by Utilizing Spiking Neural Networks; Current Perspectives. 1. 346–350. 2 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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