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Systems thinking is also logically related to knowledge and computing infrastructures necessary to link networks of researchers in their collaborative work.
The consequence of the different time scales on which scientific knowledge and computing technology evolve is that we are losing scientific knowledge encoded in the form of software faster than it can be integrated into the reformulation process of science.
Second, even if a researcher acquired the related background knowledge and computing skills, it is very time-consuming to build a predictive model as a number of steps are needed, including molecule representation, feature filtering, selection of a suitable machine learning method, prediction of new molecules, and relevant statistical analysis.
The words of Box and Draper (1987) a quarter of a century ago still capture very well the need for humility but also courage when using increasingly complex biological knowledge and computing tools in the study of infections and cancer: 'Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful.' The authors declare no conflict of interest.
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These whole-metabolite signals were simulated with the software package NMR-SCOPE [27], which uses advanced prior knowledge and computes theoretical metabolite signals in terms of spin Hamiltonian parameters [28].
After LDPC decoding, the extrinsic output E 1 becomes the a priori input A 2. The FF decoder takes channel observations y c h,i and a priori knowledge A 2, and computes the extrinsic output E 2 as: L^{0}(C_{2})=L y_{ch,i})+L^{0}(A_{2}).
In this paper, a new model is proposed, does not need any prior knowledge and the computing complexity is O(nm) for a collection of m documents with n keywords.
As the amount of information, users and computed knowledge scales exponentially, can paid sponsors support the tool?
Subsequently, the receiver can exploit the knowledge of P(O) and compute the equalizer matrix H ̂ eq = diag 1 ĥ 1, …, 1 ĥ N o ∈ C N o × N o, with ĥ k given by ĥ k = 1 R p ( O ) ∑ m = 1 R p ( O ) P ̂ ( O ) k, m P ( O ) k, m, ∀ k ∈ 1, N o.
MiRanda is a bioinformatic tool for finding genomic targets for microRNAs that incorporates current biological knowledge on target rules and computes optimal sequence complementarity between a set of mature microRNAs and a given mRNA using a weighted dynamic algorithm [ 80- 82].
miRanda is an algorithm for finding genomic targets for microRNAs that incorporates current biological knowledge on target rules and computes optimal sequence complementarity between a set of mature microRNAs and a given mRNA using a weighted dynamic programming algorithm.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com