lncrna-protein interactions predicting algorithm
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations
A Novel Approach Based on Bipartite Network Recommendation and KATZ Model to Predict Potential Micro-Disease Associations Shiru Li 1, Minzhu Xie 1, Xi ......
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction
Graph regularized non-negative matrix factorization with prior knowledge consistency constraint for drug-target interactions prediction Junjun Zhang 1 ......
Drug response prediction using graph representation learning and Laplacian feature selection
Drug response prediction using graph representation learning and Laplacian feature selection Minzhu Xie 1 2, Xiaowen Lei 3, Jianchen Zhong 3, Jianxing ......
Predict potential miRNA-disease associations based on bounded nuclear norm regularization
Predict potential miRNA-disease associations based on bounded nuclear norm regularization Yidong Rao 1, Minzhu Xie 1, Hao Wang 1 Affiliations expand P ......
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning
Predicting gene expression from histone modifications with self-attention based neural networks and transfer learning Yuchi Chen 1, Minzhu Xie 1, Jie ......
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm
LPI-IBWA: Predicting lncRNA-protein interactions based on an improved Bi-Random walk algorithm Minzhu Xie 1, Ruijie Xie 2, Hao Wang 3 Affiliations exp ......
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction
Graph regularized non-negative matrix factorization with [Formula: see text] norm regularization terms for drug-target interactions prediction Junjun ......
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier.
LDAEXC: LncRNA-Disease Associations Prediction with Deep Autoencoder and XGBoost Classifier. 作者: Lu Cuihong; Xie Minzhu 作者背景: College of Information S ......
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm
B4185. LPI-IBWA:Predicting lncRNA-protein Interactions Based on Improved Bi-Random Walk Algorithm Minzhu Xie1, Hao Wang1 and Ruijie Xi1 1Hunan Normal ......
Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis
1 前言 1.1 标题 Detecting Unknown Encrypted Malicious Traffic in Real Time via Flow Interaction Graph Analysis 1.2 摘要 为了保护网络的机密性和隐私性，目前互联网上的流量被广泛地加密。然而，流量 ......
2023ICCV_FSI Frequency and Spatial Interactive Learning for Image Restoration in Under-Display Cameras
三. Network 1. 2. FLB： 没看懂是怎么分离的水平和竖直方向 3. SLB：每一层保留一半的通道特征用于细化，其余的在特征重构后输出（没看懂）。 Multi-distillation Network 超分辨网络的Multi-distillation Network(2019ACMMM ......
论文：Predicting Optical Water Quality Indicators from Remote Sensing Using Machine Learning Algorithms in Tropical Highlands of Ethiopia
水刊，中科院都没有收录。不属于sci。 吃一堑长一智，以后先看属于哪个期刊的。总是忘记。 期刊：Hydrology 浪费时间，啥也没有，没有创新点，就一点点的对比工作量。 “Predicting Optical Water Quality Indicators from Remote Sensing ......
论文：Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network
题目“Predicting the performance of green stormwater infrastructure using multivariate long short-term memory (LSTM) neural network” (Al Mehedi 等, 2023, ......
论文：Multistep ahead prediction of temperature and humidity in solar greenhouse based on FAM-LSTM model
Multistep ahead prediction of temperature and humidity in solar greenhouse based on FAM-LSTM model 基于 FAM-LSTM 模型的日光温室温湿度多步提前预测 题目：“Multistep ahead pr ......
warning: Signature not supported. Hash algorithm SHA1 not available 问题解决
在使用Rocky Linux 安装服务的时候碰到此问题，记录下 解决方法 update-crypto-policies --set LEGACY 参考资料 https://www.redhat.com/en/blog/rhel-security-sha-1-package-signatures-di ......
Princeton Algorithms, Part I week3 Quick Sort
Quick Sort 今天学习quick sort，quick sort的基本思想是有一个数组，先shuffle以后，保证数组的item位置是均匀分布的，选择一个item然后，把所有比这个item大的放在item右边，所有比这个item小的放在左右，然后递归的进行这个操作，如下图所示 这里面的par ......
(段设期中复习) Great Ideas in Algorithm Analysis: Midterm Review
Distance Algorithms Basic sampling lemma: Let \(S_1,\dots,S_n \subset [n]\) be sets of size at least \(D\), then randomly choose \(c (n/D) \log n\) el ......
Princeton Algorithms, Part I week2 Merge Sort
Merge sort 今天学习merge sort 这个排序算法的思想就是，不停的将数组二分，再将两个子数组不停归并。其中有一个操作叫merge如下图所示。左右两边两个部分是有序的，然后思想也很简单 有两个指针i和j，i指向lo，j指向mid+1，然后比较两个指针所指的大小，如果小就选出来排到数组中 ......
洛谷 P6960 [NEERC2017] Interactive Sort
洛谷传送门 NOIP 模拟赛 T2。随机化交互好题。 令 \(a\) 为原题面中的 \(e\)，\(b\) 为原题面中的 \(o\)。 显然可以使用 \(\left\lceil\frac{n}{2}\right\rceil\) 次询问求出 \(a\) 中任意其中一个元素的值，全部问一遍 \(a_i\ ......
[洛谷 P3481] [BZOJ1118] [POI2009] PRZ-Algorithm Speedup
题目描述 你需要计算一个函数 \(F(x, y)\)，其中 \(x, y\) 是两个正整数序列。 bool F(std::vector<int> x, std::vector<int> y) { if (W(x).size() != W(y).size()) return false; if (W( ......
Paper Reading: A hybrid deep forest-based method for predicting synergistic drug combinations
为了解决联合用药数据的不平衡、高维、样本数量有限的问题，本文首先构建了一个由药物的物理、化学和生物特性组成的特征集，包括了丰富的生物学信息。特征空间的每个维度都有特定的含义，便于进行可解释性分析，找出预测过程中的关键特征。针对这种不平衡的高维中型数据集，提出了一种改进的基于 Deep Forest ... ......
JSch连接SSH问题Exception:Algorithm negotiation fail
Java连接RPA系统，由于特殊原因不能使用接口，决定用openssh连接，定时读取与推送。 注意点： 1、C:\ProgramData\ssh\sshd_config 配置 2、ssh-keygen -t rsa生成秘钥方式 3、生成之后追加到authorized_keys编码格式 utf-8 4 ......
Linkless Link Prediction via Relational Distillation
目录概符号说明LLP代码 Guo Z., Shiao W., Zhang S., Liu Y., Chawla N. V., Shah N. and Zhao T. Linkless link prediction via relational distillation. ICML, 2023. 概 ......
Proj. Unknown: Deciding Differential Privacy of Online Algorithms with Multiple Variables
Paper https://arxiv.org/abs/2309.06615 Abstract 背景： 自动机A被称作查分隐私自动机：当对某些D，对任何隐私预算ε>0,该自动机是Dε-differentially private( A DiP automaton is a parametric au ......
Princeton Algorithms, Part I week2 stack&queue
stack:先进后出 queue:先进先出 首先是stack 有两种实现方式，第一种是用链表，第二种是用数组。 Stack: linked-list representation stack: array implementation 上面这个实现是固定长度的array implementation ......
基于rk3588----i2c驱动框架学习（2）-总线驱动 algorithm 分析
rk3588 i2c algorithm 分析 来了来了，上次分析完i2c的驱动框架 今天我们就看看i2c的algorithm是如何实现的 static const struct i2c_algorithm rk3x_i2c_algorithm = { .master_xfer = rk3x_i2c ......
城市时空预测的统一数据管理和综合性能评估 [实验、分析和基准]《Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis & Benchmark]》
2023年11月1日，还有两个月，2023年就要结束了，希望在结束之前我能有所收获和进步，冲呀，老咸鱼。 摘要 解决了访问和利用不同来源、不同格式存储的不同城市时空数据集，以及确定有效的模型结构和组件。 1.为城市时空大数据设计的统一存储格式“原子文件”，并在40个不同的数据集上验证了其有效性，简化 ......
[PG] Function Candidates Selection Algorithm
Function Candidates Selection Algorithm environment setup In lightdb orafce extension, execute sql below, CREATE DOMAIN oracle.clob AS TEXT; -- versio ......
wpf Interaction Triggers 绑定任意方法、任意Command
framework版本引入命名空间 通过在代码中引入System.Windows.Interactivity.dll,引入了这个dll后我们就能够使用这个里面的方法来将事件映射到ViewModel层了，我们来看看具体的使用步骤，第一步就是引入命名控件 xmlns:i="clr-namespace:S ......
2023ACMMM_Mutual Information-driven Triple Interaction Network for Efficient Image Dehazing
一. Motivation 之前网络存在的缺点： 1. 使用的有限的频域信息 2. 不充足的信息交互 ： (1) 第一阶段的输出直接作为第二阶段的输入，忽略了中间特征从早期到后期的传播 (2) 在编码器解码器结构同尺度之间进行特征融合，忽略了阶段内和跨阶段的跨尺度信息交换 3. 严重的特征冗余：中间 ......