Nature

ss-v2ray

A fork of MSA by Sergey Senkin that aims at anayzing experimental / de novo extracted mutational signatures through screening version 7 of PCAWG mutational matrices. The pipeline can be used with simple signatures (which is easier to link to COSMIC signatures that are official only in 96 channels) but is interesting to deal with strand biased signatures in 192 channels. The 192 version of COSMIC signatures, which were collected from COSMIC versions 3.1-3.3, are also available on the repository

近日，华裔教授姜炜文再获量子计算革命性突破，在QuantumWeek上开源了首个量子神经网络设计栈，加速了神经网络在量子计算机上的发展。 神经网络是当下计算应用中发展最快，使用最广的机器学习算法。然而，随着应用不断复杂化导致网络结构不断扩大，存储性能瓶颈已逐渐凸显。 在传统计算平台上，N个数字比特只