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reproducibility-fbb-msu Goto Github PK

repos: 25.0 gists: 0.0

Type: Organization

Bio: We promote learning of python programming for computational biology through reproducibility of recent papers.

reproducibility-fbb-msu's Projects

ab-initio-protein-structure-prediction icon ab-initio-protein-structure-prediction

Using materials and methods of the article "Ab initio protein structure prediction of CASP III targets using ROSETTA" written by Kim T. Simons, Rich Bonneau, Ingo Ruczinski and David Baker, we conducted ab initio folding to generate structures consistent with both the local and nonlocal interactions responsible for protein stability. To generate structures consistent we've implemented 3, 5 and 9 residue fragments of known structures into local sequences similar to the target sequence using a Monte Carlo simulated annealing procedure with further refinement of the obtained complete tertiary structure according to the article.

camisim_reproducibility icon camisim_reproducibility

To reproduce some results from "CAMISIM: simulating metagenomes and microbial communities". Authors: Simon Konnov, Ciara Makievskaya, Ruslan Gumerov

cichlidsgeneflow icon cichlidsgeneflow

Воспроизведение Fig 3. из статьи Whole-genome sequences of Malawi cichlids reveal multiple radiations interconnected by gene flow

crispr-cas3 icon crispr-cas3

Reproducibility of some plots from "Cas3-Derived Target DNA Degradation Fragments Fuel Primed CRISPR Adaptation" paper (Künne et al., 2016 Molecular Cell) for the purpose of learning Python for computational biology.

freepsi icon freepsi

Трифонова, Волобуева

genome-expansion icon genome-expansion

To reproduce some plots from the article "Evolutionary Rewiring of Human Regulatory Networks by Waves of Genome Expansion" (Marnetto et al, Am J Hum Genet, 2018)

giggle icon giggle

Reproducibility of visualization of GIGGLE scores from the relationships between 15 genomic states across different cell types and tissues predicted by ChromHMM for Roadmap and MyoD ChIP-seq peaks

goatools_repr icon goatools_repr

Воспроизведение некоторых результатов из статьи про GOATOOLS: A Python library for Gene Ontology analyses (DOI:10.1038/s41598-018-28948-z)

instructions icon instructions

This repo contains instructions for the students about git usage and projects update.

phenograph icon phenograph

Single cell RNA-seq and clusterization (phenograph)

ribo-seq icon ribo-seq

Reproducibility of some plots from "Clarifying the Translational Pausing Landscape in Bacteria by Ribosome Profiling" paper (Mohammad et al., 2016 Cell Reports) for the purpose of learning Python for computational biology.

rna-dna icon rna-dna

Reproducibility of some plots from GRID-Seq paper (Xiao Li et al., 2018 Nature Biotechnology) for the purpose of learning Python for computational biology.

scscope icon scscope

Scalable analysis of cell-type composition from single-cell transcriptomics using deep recurrent learning

single-cell-alzheimer icon single-cell-alzheimer

To reproduce some results from "A Unique Microglia Type Associated with Restricting Development of Alzheimer’s Disease" (H. Keren-Shaul et al, Cell, 2017)

tads icon tads

Reproducibility of some plots from "Comparison of computational methods for Hi-C data analysis" paper (Forcato et al., 2017 Nature Methods) for the purpose of learning Python for computational biology.

treewas icon treewas

Test of treeWAS tool described in the paper "A phylogenetic method to perform genome-wide association studies in microbes that accounts for population structure and recombination" (Caitlin Collins, Xavier Didelot, 2018, PLOS Computational Biology).

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