anguelos

cv_ws_2023

winterschool 2023

czeck_bavaria

Utilities for the project

dagtasets

dl_sem_pytorch

Notebooks For Pytorch tutorials

embedding_map

Experiments on mean Average Precision and embeddings

fargv

fast_argv

frat

Fast Rectangle Annotation Tool

kagglito

when I grow up I am going to be kaggle

tormentor

Pytorch augmentation

yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

anguelos/tormentor

Pytorch augmentation

anguelos/frat

Fast Rectangle Annotation Tool

anguelos/dl_sem_pytorch

Notebooks For Pytorch tutorials

anguelos/cv_ws_2023

winterschool 2023

anguelos/fargv

fast_argv

anguelos/czeck_bavaria

Utilities for the project

anguelos/dagtasets

anguelos/ambiguous_dates

Demo of user interaction for ambiguous dates

anguelos/bilde

Buffer Imaging Library, Dirty and Extendable

anguelos/wi19_evaluate

Evaluation code for the ICDAR 2019 Writer Identification Competition

anguelos/yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

anguelos/Alpaca-LoRA-Serve

Alpaca-LoRA as Chatbot service

anguelos/Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273

RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.

anguelos/bkang

A simple backup utility

anguelos/cb_backend

anguelos/cbdia_retrieval

anguelos/cbdia_service

service for large scale wordspotting

anguelos/ddpa_cei2json

extracts fundamental data from cei and stores them in JSON

anguelos/ddpa_tokenization

A scaffold to be the DiDip tokenazation repo

anguelos/flask-iiif

Flask-IIIF is permitting easy integration with the International Image Interoperability Framework (IIIF) API standards.

anguelos/graz_cv_ws2023

anguelos/histdiads

historical document datasets

anguelos/kornia

Open Source Differentiable Computer Vision Library for PyTorch

anguelos/kraken

OCR engine for all the languages

anguelos/palexploration

A tool for interactive data exploration

anguelos/pero-ocr

anguelos/pytorch-phocnet

PHOCNet implementation in Pytorch based on Sudholt's implementation

anguelos/resolution_regressor

A CNN tat learns to infer PPIs on a document image from

anguelos/rpack

pack rectangles of different sizes into an area as small as possible

anguelos/stanford_alpaca

Code and documentation to train Stanford's Alpaca models, and generate the data.