找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Bioinformatics Research and Applications; 16th International S Zhipeng Cai,Ion Mandoiu,Xuan Guo Conference proceedings 2020 Springer Nature

[復制鏈接]
樓主: 戰(zhàn)神
11#
發(fā)表于 2025-3-23 11:46:51 | 只看該作者
12#
發(fā)表于 2025-3-23 16:52:07 | 只看該作者
13#
發(fā)表于 2025-3-23 19:43:20 | 只看該作者
Isoform-Disease Association Prediction by Data Fusion,ion term to dispatch gene-disease associations to individual isoforms, and reversely aggregate these dispatched associations to affiliated genes. Next, it fuses different genomics and transcriptomics data to replenish gene-disease associations and to induce a linear classifier for predicting isoform
14#
發(fā)表于 2025-3-24 01:09:33 | 只看該作者
EpIntMC: Detecting Epistatic Interactions Using Multiple Clusterings,a and reduce the chance of filtering out potential candidates overlooked by a single clustering. In the search stage, EpIntMC applies Entropy score to screen SNPs in each cluster, and uses Jaccard similarity to merge the most similar clusters into candidate sets. After that, EpIntMC uses exhaustive
15#
發(fā)表于 2025-3-24 04:52:46 | 只看該作者
16#
發(fā)表于 2025-3-24 10:01:50 | 只看該作者
Ess-NEXG: Predict Essential Proteins by Constructing a Weighted Protein Interaction Network Based ontial proteins. In Ess-NEXG, we construct a reliable weighted network by using these data. Then we use the node2vec technique to capture the topological features of proteins in the constructed weighted PPI network. Last, the extracted features of proteins are put into a machine learning classifier t
17#
發(fā)表于 2025-3-24 12:14:36 | 只看該作者
18#
發(fā)表于 2025-3-24 18:19:00 | 只看該作者
SVLR: Genome Structure Variant Detection Using Long Read Sequencing Data,e classic structural variants that can be detected by state-of-the-art methods (e.g., SVIM and Sniffles), our experiments demonstrate recall improvements of up-to . without harming the precisions (i.e., above .). We also point out three directions to further improve structural variant detection in t
19#
發(fā)表于 2025-3-24 20:51:36 | 只看該作者
Prediction of Drug-Target Interaction via Laplacian Regularized Schatten-p Norm Minimization,ew drug/target cases by combining the loss function with a Laplacian regularization term. Finally, we numerically solve the LRSpNM model by an efficient alternating direction method of multipliers (ADMM) algorithm. Performance evaluations on benchmark datasets show that LRSpNM achieves better and mo
20#
發(fā)表于 2025-3-25 00:13:37 | 只看該作者
 關于派博傳思  派博傳思旗下網站  友情鏈接
派博傳思介紹 公司地理位置 論文服務流程 影響因子官網 吾愛論文網 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經驗總結 SCIENCEGARD IMPACTFACTOR 派博系數 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網安備110108008328) GMT+8, 2025-10-8 20:03
Copyright © 2001-2015 派博傳思   京公網安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
孟村| 孝昌县| 驻马店市| 新绛县| 巫山县| 阿瓦提县| 蛟河市| 德庆县| 宁陵县| 辽源市| 乌拉特前旗| 苏州市| 莱州市| 馆陶县| 通许县| 孙吴县| 民丰县| 泌阳县| 苗栗县| 南宁市| 景宁| 抚州市| 嘉定区| 宽城| 武邑县| 罗江县| 长子县| 来安县| 贵定县| 方山县| 南宁市| 左贡县| 杭锦旗| 晋中市| 凌源市| 夏邑县| 泰顺县| 铜山县| 乡宁县| 宜丰县| 丁青县|