Primer3 is a command line tool to select primers for polymerase chain reaction (PCR).

A tool for populating templates with environment variables and Vault values

Open Source PCR machine for DIY Recombinant Genetics

Pytorch implementation of DeePromoter Active sequence detection for promoter(DNA subsequence regulates transcription initiation of the gene by controlling the binding of RNA polymerase)

RNA dependent RNA Polymerase Palmprint Analysis

A mutation rate model at the basepair resolution identifies the mutagenic effect of Polymerase III transcription

A deep learning model for RNA polymerase II (Pol II) pausing prediction

A primer design algorithm for Multiplex Polymerase Chain Reaction (PCR).

Caizzi, Monteiro-Martins (2021)

Engineer biology organisms with Polymerase-go Workbench, powered by 'Poly' and super-fast 'Go' backend.

Transcription fit (Tfit) utilizes a generative model of RNA Polymerase to identify sites of divergent transcription in assays like GRO-seq, PRO-seq and GRO-cap

KAS-pipe is an analysis pipeline for KAS-seq data. KAS-seq allows rapid (within 5 min), sensitive and genome-wide capture and mapping of ssDNA produced by transcriptionally active RNA polymerases, DNA replication or other processes in situ.

A service-oriented, Objective C and Swift dependency injection framework, for macOS and iOS.

Data -> DNA -> Data

Simulates the reactions between primers and template strands in polymerase chain reaction

The 2019 novel coronavirus (COVID-19) presents several unique features. While the diagnosis is confirmed using polymerase chain reaction (PCR), infected patients with pneumonia may present on chest X-ray and computed tomography (CT) images with a pattern that is only moderately characteristic for the human eye. Bilateral multiple lobular and subsegmental areas of consolidation can be observed in COVID-19 patients. The following model aims to present a neural network aimed to detect COVID-19 cases through chest X-Rays. While a neural network to detect COVID-19 cases has been published, the following model has a much higher accuracy. Out model uses a sample of 100 COVID-19 positive cases and 100 COVID-19 negative cases, and has an accuracy of 91% . Of the true positive patients, the model had an accuracy of 100%, and of the true negative patients, the model had an accuracy of 80%. Given the fact that the data is limited, the model can be improved in the near future for rapid diagnosis of COVID-19 cases with an extremely low rate of false positives. While the model may still be in an initial phase of development, it can be put to practical use soon with enough training and accuracy.

Tutorial that demonstrates the modeling of RNA Polymerase II using Electron Microscopy density and chemical crosslinks

Code accompanying 'Increased somatic mutation burdens in normal human cells due to defective DNA polymerases' (Robinson, Coorens, Palles et al., Nature Genetics, 2021)

MySQL backup manager integrated with Percona Xtrabackup and mysqldump

Exact Python reproduction of the NEB Tm Calculator for PCR primer analysis with all NEB polymerases

Simulator of polymerase dynamics during UV damage and repair

a roadmap for building a controlled polymerase

No description available

Snakemake pipeline to evaluate polymerase-amplified HiFi read sets

NSGA-II Sequence Generation Software for Polymerase Strand Displacement CRNs.

A python script for detecting genuine Polymerase III-transcribed SINEs from RNA-seq data at single locus resolution

A python script to automate the process of analyzing data from a standard quantitative polymerase chain reaction assay.

The impact of DNA polymerase and number of rounds of amplification in PCR on 16S rRNA gene sequence data

No description available

No description available