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Titlebook: Cancer Biomarkers in Body Fluids; Biomarkers in Proxim Gabriel D. Dakubo Book 2019 Springer Nature Switzerland AG 2019 body fluid biomarker

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41#
發(fā)表于 2025-3-28 17:40:02 | 只看該作者
Calculus of Communicating Systemss book with many new results. The calculus is meant as a formal mathematical framework which can be used to specify communicating systems and to verify properties of them. A system is considered to consist of parts, each of which has an own identity, which persists through time. A system will be characterized by the actions it can perform.
42#
發(fā)表于 2025-3-28 19:32:28 | 只看該作者
Das Rohholz und seine Zurichtung,ctively evaluate the validity of the clustering results of many clustering algorithms. Experimental results on testing many types of datasets have demonstrated that the MPC index proposed in this paper is able to quickly handle datasets like spherical datasets, non-spherical datasets and real large-scale datasets.
43#
發(fā)表于 2025-3-29 02:06:42 | 只看該作者
Introductiondies infectieuses restent un fardeau inacceptable pour les populations des pays en développement. L’émergence de nouvelles maladies infectieuses constitue une autre menace qui pèse sur tous les habitants du globe et qui semble s’intensifier (Jones et al. 2008).
44#
發(fā)表于 2025-3-29 05:37:48 | 只看該作者
Min-Si Ren,Yan-Ming Zhang,Qiu-Feng Wang,Fei Yin,Cheng-Lin Liuutomotive SPICE requirements may represent, in some contexts, a target hardly achievable, or even a chimera. In this paper we present a novel automotive-specific scheme for process evaluation and improvement. This scheme has been conceived taking into account the authors experience in automotive as
45#
發(fā)表于 2025-3-29 07:24:03 | 只看該作者
46#
發(fā)表于 2025-3-29 15:09:11 | 只看該作者
47#
發(fā)表于 2025-3-29 19:32:40 | 只看該作者
48#
發(fā)表于 2025-3-29 23:29:44 | 只看該作者
49#
發(fā)表于 2025-3-30 00:53:00 | 只看該作者
Dense Module Enumeration in Biological Networks,imations to extract dense modules, our approach exactly solves the problem of dense module enumeration. Furthermore, constraints from additional information sources such as gene expression and phenotype data can be integrated, so we can systematically detect dense modules with interesting profiles.
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