WG-prices is a free and intuitive webpage where anyone can analyse the market of shared flats (WGs) in Germany. It was created out of curiosity and desire to help people understand the housing market better. With roughly 750 new offers posted everyday, the embedded database of ads is fast-growing. WG-prices can also be used as a stand alone crawler for wg-gesucht.de and/or an application that collects housing ads from wg-gesucht.de and saves them as a .csv file. You can check out the webpage here.

wg_price_predictor provides the code for selecting the best predictive model for a given data using sklearn's Pipeline module. I implemented it with WG ads collect by the WG-prices app since August 2022. Features include physical and meta information on the size and type of WG, and on other characteristics of the flatshare. On top of that, I incorporated information on surrounding city objects like streets, banks, stores, parks, lakes, etc obtained in Livablestreets. My best models can predict most WG prices in Germany within a 50€ error margin!

Livablestreets is a web service that calculates living quality in cities all over the world at streets level. This project was originally co-created with Laia Grobe, Ieva Bidermane and Nicolas Quiroga as the conclusion project for the Data Science bootcamp I completed in Jun 2022 at Le Wagon. Since then, I've continued working to improve and further develop the web service. Since September 2022 the webservice is maintained by deep-urbanism, which I am a co-founder. You can check out the webpage here.

In my profile you'll also find several repositories related to my scientific publications in the field of Molecular Biology. For an extensive list of my scientific work, please refer to Google Scholar or Orcid. Here's a list of these repositories and the respective scientific publication:

1. chvieira2/qRIC_pulldown_efficiency_2022 = Vieira-Vieira et al., Proteome-wide quantitative RNA-interactome capture identifies phosphorylation sites with regulatory potential in RBM20, Molecular Cell, 2022.
2. chvieira2/NUP85_SubCellFrac = Ravindran et al., Expanding the phenotype of NUP85 mutations beyond nephrotic syndrome to primary autosomal recessive microcephaly and Seckel syndrome spectrum disorders, Human Molecular Genetics, 2021.
3. chvieira2/pre-50S_stoichiometry = Nikolay et al., Snapshots of native pre-50S ribosomes reveal a biogenesis factor network and evolutionary specialization, Molecular Cell, 2021.
4. chvieira2/EBP1_pSILAC-AHA = Kraushar et al., Protein synthesis in the developing neocortex at near-atomic resolution reveals Ebp1-mediated neuronal proteostasis at the 60S tunnel exit, Molecular Cell, 2021.
5. chvieira2/PTex-Repo = Urdaneta et al., Purification of cross-linked RNA-protein complexes by phenol-toluol extraction, Nature Communications, 2019.
6. chvieira2/KLF4_overlap_genes = Rocha-Martins et al., De novo genesis of retinal ganglion cells by targeted expression of Klf4 in vivo, Development, 2019.