Comparative gene expression in toxic versus non-toxic strains of the marine dinoflagellate Alexandrium minutum is a research paper published in BMC Genomics (2010). On theSindex it has a DataRank of 2.6. It has been cited 82 times, with 66 citing works in its 1-hop citation network. Its calibrated FAIR score is 55/100.
Abstract Background The dinoflagellate Alexandrium minutum typically produces paralytic shellfish poisoning (PSP) toxins, which are known only from cyanobacteria and dinoflagellates. While a PSP toxin gene cluster has recently been characterized in cyanobacteria, the genetic background of PSP toxin production in dinoflagellates remains elusive. Results We constructed and analysed an expressed sequence tag (EST) library of A. minutum, which contained 15,703 read sequences yielding a total of 4,320 unique expressed clusters. Of these clusters, 72% combined the forward-and reverse reads of at least one bacterial clone. This sequence resource was then used to construct an oligonucleotide microarray. We analysed the expression of all clusters in three different strains. While the cyanobacterial PSP toxin genes were not found among the A. minutum sequences, 192 genes were differentially expressed between toxic and non-toxic strains. Conclusions Based on this study and on the lack of identified PSP synthesis genes in the two existent Alexandrium tamarense EST libraries, we propose that the PSP toxin genes in dinoflagellates might be more different from their cyanobacterial counterparts than would be expected in the case of a recent gene transfer. As a starting point to identify possible PSP toxin-associated genes in dinoflagellates without relying on a priori sequence information, the sequences only present in mRNA pools of the toxic strain can be seen as putative candidates involved in toxin synthesis and regulation, or acclimation to intracellular PSP toxins.
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Calibrated FAIR score — a parallel quality metric, independent of the DataRank citation score. See the full evaluation →
Base Score Contribution
0.663
From this paper's citation signal
Citation Network Contribution
2.0
From 60 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 25% comes from its base citations and 75% from the citation network (60 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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