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Thomas Schmidt

Researcher at Swiss Institute of Bioinformatics

Publications -  52
Citations -  3487

Thomas Schmidt is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Gene & Thermal energy storage. The author has an hindex of 23, co-authored 50 publications receiving 2373 citations. Previous affiliations of Thomas Schmidt include Lüneburg University & University of Zurich.

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Structural and functional development of twelve newly established floodplain pond mesocosms

TL;DR: In this article , the authors report results of a comprehensive ecosystem development monitoring for twelve floodplain pond mesocosms (FPM; 23.5 m × 7.5m × 1.5 meters each) located in southwestern Germany.
Posted ContentDOI

Disentangling the impact of environmental and phylogenetic constraints on prokaryotic strain diversity

TL;DR: It is shown that many pan-genome features such as functional diversity and core genome nucleotide diversity are correlated to each other, and habitat flexibility as approximated by species ubiquity is associated with several pan- Genome features, particularly core genome size.
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The genes coding for tRNATyr of Drosophila melanogaster: Localization and determination of the gene numbers

TL;DR: Transfer RNATyr (anticodon GΨA) was isolated from Drosophila melanogaster by means of Sepharose 4B, RPC-5, and polyacrylamide gel electrophoresis and restriction enzyme analysis of genomic DNA indicated that the haploid Dosophila genome codes for about 23 tRNATyr genes.
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treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses.

TL;DR: TreeclimbR as mentioned in this paper proposes multiple candidates that capture the latent signal and pinpoints branches or leaves that contain features of interest in a data-driven way, in a hierarchical tree of entities.
Posted ContentDOI

A Family of Interaction-Adjusted Indices of Community Similarity

TL;DR: It is argued that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.