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3dpredictor

3DPredictor - a computational approch to predict spatial interactions of chromatin based on epigenetic data

abc

Allele-specific Binding from Chip-seq

abide

ABIDE Preprocessed Initiative

active-learning

activelearning

Active Learning in R

ad_classification_vae

Deep spectral-based shape features for Alzheimer’s Disease classification

adni-netwas

Repository associated with Song et al. manuscript describing a Network-wide Association Study of ADNI Cohorts.

als-deeplearning

Deep learning frame for genetic disease

alzheimers_diagnosis_stagedetermination

E6893 Final Project for ja3130, mn2769, and hz2441 (Project ID: 201712-18)

alzheimers_disease_progression

Code for analysis of ADNI data

ampad-diffexp

Code base for performing covariate adjustments and differential expression analysis of the RNAseq data from AMP-AD.

aparent

APA Regression Net - Predict and Engineer Alternative Polyadenylation

aqua-hichip

Bioinformatic tools (R scripts) for the analysis of Absolute Quantification of Architecture (AQuA-HiChIP) style data.

as_variant_pipeline

Allele specific variant pipeline

asprin

aspu

An R package for adaptive sum of powered score test(ASPU) in genetic association studies.

atac-seq-pipeline

ENCODE ATAC-seq pipeline

atmpra

Analysis Toolset for Massively Parallel Reporter Assay data

augmentor

Image augmentation library in Python for machine learning.

autoencoder_classifier

Autoencoder model for rare event classification

awesome-multimodal-ml

Reading list for research topics in multimodal machine learning

awesome-semi-supervised-learning

:scroll: An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.

baalchip

bam-readcount

count DNA sequence reads in BAM files

basenji

Sequential regulatory activity predictions with deep convolutional neural networks.

basset

Convolutional neural network analysis for predicting DNA sequence activity.

bayesian-neural-network-blogpost

Building a Bayesian deep learning classifier

benchmarking_variant_callers

In this study, we perform systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We evaluate the performances of these tools in different read depths, genomic contexts, functional regions and variant allele frequencies.

bichrom

Interpretable bimodal network for transcription factors binding site prediction

bioinfor-deepatt

DeepATT, a hybrid deep neural network method for identifying functional effects of DNA sequences.