Search alternatives:
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
gpu optimization » _ optimization (Expand Search), fox optimization (Expand Search), art optimization (Expand Search)
based method » based methods (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
genes based » gene based (Expand Search), lens based (Expand Search)
based gpu » based gpm (Expand Search), based gas (Expand Search), based g (Expand Search)
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
gpu optimization » _ optimization (Expand Search), fox optimization (Expand Search), art optimization (Expand Search)
based method » based methods (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
genes based » gene based (Expand Search), lens based (Expand Search)
based gpu » based gpm (Expand Search), based gas (Expand Search), based g (Expand Search)
-
81
-
82
<i>OptRAM</i>: <i>In-silico</i> strain design via integrative regulatory-metabolic network modeling
Published 2019“…To address challenges in metabolic engineering, computational strain optimization algorithms based on genome-scale metabolic models have increasingly been used to aid in overproducing products of interest. …”
-
83
DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP
Published 2022“…</p><p>Methods: Transcriptomic data of patients with HCC were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. …”
-
84
-
85
-
86
-
87
-
88
-
89
-
90
-
91
-
92
-
93
-
94
-
95
-
96
Simulated Design–Build–Test–Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering
Published 2023“…Simultaneous optimization of a large number of pathway genes often leads to combinatorial explosions. …”
-
97
Table1_Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms.XLSX
Published 2023“…</p><p>Methods: Ferroptosis-related genes were retrieved from the FerrDb and KEGG databases. …”
-
98
Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm
Published 2023“…This work mainly focuses on the following aspects: (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks. (2) Isolated genes were properly processed by the IDS to optimize the network structure. (3) The performance of IMBDANET was assessed with extensive experiments. …”
-
99
Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm
Published 2023“…<ul><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wei-Liu-Aff1-Aff2" target="_blank">Wei Liu</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Yi-Jiang-Aff1" target="_blank">Yi Jiang</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Li-Peng-Aff3" target="_blank">Li Peng</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Xingen-Sun-Aff1" target="_blank">Xingen Sun</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wenqing-Gan-Aff1" target="_blank">Wenqing Gan</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Qi-Zhao-Aff4" target="_blank">Qi Zhao</a> </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Huanrong-Tang-Aff1" target="_blank">Huanrong Tang</a></li></ul><p dir="ltr">A novel network inference method based on the improved MB discovery algorithm, IMBDANET, was proposed for improving gene regulatory networks. …”
-
100