protein or nucleotide sequence against a target protein or nucleotide sequence by an alignment algorithm, the method comprising the step of combining two or more alignment results into a single alignment result for each specific region of sequence alignment identified between query and target sequences...
invention relates to a method for reducing the number of results generated by the alignment of a query protein or nucleotide sequence against a target protein or nucleotide sequence by an alignment algorithm, the method comprising the step of combining two or more alignment results into a single ...
(Single choice question) Which kind of clustering method uses a multi-resolution grid data structure to quantify the space into a limited number of units? () A. Partition clustering B. Hierarchical clustering C. Grid-based clustering D. Density-based clustering ...
Using STO 4G double ζ expansive basis set,calculate the molecular orbits with a single configuration by SCF method. 选用STO4G双Zeta扩展基组,用单组态自洽场方法计算了分子轨道,然后作较大规模的组态相互作用计算,得到分子电子态的能量,并与分子的离解产物原子进行比较,进而计算出电子态的各光谱常数。 2....
Deep clustering for single-channel speech separation Implement of "Deep Clustering Discriminative Embeddings for Segmentation and Separation" Requirements seerequirements.txt Usage Configure experiments in .yaml files, for example:train.yaml Training: ...
Single-cell multimodal sequencing technologies are developed to simultaneously profile different modalities of data in the same cell. It provides a unique opportunity to jointly analyze multimodal data at the single-cell level for the identification of distinct cell types. A correct clustering result is...
A common analysis of single-cell sequencing data includes clustering of cells and identifying differentially expressed genes (DEGs). How cell clusters are defined has important consequences for downstream analyses and the interpretation of results, but is often not straightforward. To address this difficu...
single﹙alued variablesThe main objective of the data clustering is to classify a set of objects in groups, minimizing an objective criterion that measures the homogeneity of the partition of the objects. This chapter presents a novel﹚eighted multi‐table clustering method that is able to ...
AGNES initially takes each object as a cluster, afterwards the clusters are merged step by step according to certain criteria, using a single-link method. The level of similarity of the two clusters is measured by the similarity of the nearest pair of data points in the two different clusters...
In the existing research, the classification effect of the method combining resampling with the classification idea improvement strategy may be better than that of a single strategy. In reference [4], combining random undersampling and ensemble learning methods, EasyEnsemble and BalanceCascade methods ...