From Algorithms to Discovery in Genome-Scale Biology and Medicine 2022
2022-07-05..2022-07-12
Berkeley, United States
who it's for
single-cell genomics researchers, computational biologists, cancer genomics researchers, translational clinico-genomics scientists, systems biologists, proteomics researchers, bioinformatics engineers
topics
spatial omics clustering; spatial transcriptomics deconvolution; cis-regulatory element conservation; chemical bioactivity embeddings; integrated iCell network analysis; single-cell 3D epigenomics imputation; reference-free k-mer variant detection; in silico clinical trial platforms; phospho-QTL genetic mapping; tyrosine kinase interactome mapping; ancient DNA phenotype inference; variant deleteriousness prediction
| title | author | length |
|---|---|---|
| BANKSY: A Spatial Omics Algorithm that Unifies Cell Type Clustering and Tissue Domain Segmentation | Shyam Prabhakar | 47m |
Algorithm constructs a product space of cell and neighborhood transcriptomes by appending k‑nearest‑neighbor averaged expression to each cell, then runs… | ||
| Spatial Transcriptomics Identifies Neighbourhoods and Molecular Markers of Alveolar Damage... | Martin Hemberg | 30m |
Built a 600,000‑cell single‑cell lung atlas from 15 studies and applies NanoString GeoMx (≈18,000 probes) to 233 ROIs from 33 post‑mortem lungs scored as PRES… | ||
| Landscapes of Human cis-regulatory Elements and Transcription Factor Binding Sites... | Zhiping Weng | 39m |
Built a registry of nearly 1 million candidate cis‑regulatory elements from ENCODE data, then aligns them with a 240‑mammal CACTUS alignment and mammal PhyloP… | ||
| Formatting Biological Big Data to Enable (Personalized) Systems Pharmacology | Patrick Aloy | 36m |
A publicly released resource called Chemical Checker turns experimental bioactivity for ~1,000,000 small molecules into 25 complementary 128‑dimensional vector… | ||
| Understanding Molecular Complexity for Precision Medicine | Natasa Przulj | 33m |
Graph topology methods convert heterogeneous omics into an iCell integrated network using graph-regularized NMTF and graphlet counts; the top 500 most rewired… | ||
| Machine Learning for Single-Cell 3D Epigenomics | Jian Ma | 35m |
Presents a concrete pipeline: a hypergraph model where hyperedge = cell+bin+bin encodes each single-cell Hi‑C contact, a graph/neural embedding (Higashi) that… | ||
| A Statistical, Reference-Free Algorithm Subsumes Myriad Problems in Genome Science | Julia Salzman | 27m |
A unifying probabilistic model and a reference-free algorithm called gnomAD operates on raw FASTQ k-mers, builds contingency tables of upstream/downstream… | ||
| Using Large-Scale Clinico-Genomics Data for in silico Clinical Trials and Precision Oncology | James Zou | 35m |
A computational platform called Trial Pathfinder uses Flatiron EHR plus Foundation Medicine tumor panels to run millions of in silico trials, matching cohorts… | ||
| Long-Range Propagation of Genetic Effects in Molecular Networks | Andreas Beyer | 33m |
Cross of BY and RM yeast strains, matched RNA, protein (SWATH/DIA) and the first phospho-QTL layer, uses regression to remove abundance effects and random… | ||
| A Binary Quantitative Interaction Mapping Approach: Elucidating Multiprotein Complexes in... | Erich Wanker | 37m |
Automated yeast two‑hybrid screens test ~70,000 pairings per week from a 17,000 human cDNA array but detect only ~20–25% of known interactions; a new LUCY… | ||
| A Tyrosine Kinase Protein Interaction Map Reveals Targetable EGFR Network Oncogenesis in Lung Cancer | Sourav Bandyopadhyay | 33m |
A systematic AP‑MS survey of 90 tyrosine kinases in HEK293 cells (about 400+ AP‑MS experiments) yields a scored interaction map (CompPASS cutoff ~2.5) that… | ||
| Computational Approaches to Study Interactions Between Mutagenic Processes and Cellular Processes | Teresa Przytycka | 39m |
Cancer mutational patterns are treated as quantitative traits and linked to expression, cell composition, and mutated subnetworks using concrete tools: 96… | ||
| Mapping Biological Pathways Using Systematic Genetics and Cell Biology | Brenda Andrews | 34m |
Systematic double-mutant mapping uses synthetic genetic array (SGA) and a colony size fitness proxy to quantify genetic interactions in yeast and yields ~1… | ||
| Algorithms for Inferring Phenotypes from Ancient DNA | Tony Capra | 43m |
A deep learning pipeline predicts 3D Hi-C contact maps from 1 Mb of DNA and applies Akita deep learning model to Neanderthal, Denisovan and diverse modern… | ||
| Predicting the Deleteriousness of Genomic Variants – Big and Small | Martin Kircher | 27m |
CADD scores short variants by contrasting fixed human‑derived alleles with simulated de novo changes and integrates many annotations on a single continuous… | ||
| Determining the Molecular Intermediates Between Genotype and Phenotype | David Knowles | 25m |
Uses pooled RIP-seq on nine iPSC lines plus genotype estimates and a Bayesian beta‑binomial model (implemented in Pyro) to call allele‑specific RBP binding… | ||
| How Genome 3D Organization Regulates Alternative Splicing? | Gil Ast | 36m |
Study demonstrates that genome 3D position links GC architecture to splicing mode: low-GC differential versus level GC architectures map to the nuclear… | ||
| Distinct Gene Programs Underpinning ‘Disease Tolerance’ and ‘Resistance’ Against Infections | Irit Gat-Viks | 25m |
Identifies two co-activated lung gene programs — T program (disease tolerance) and R program (pathogen resistance) — from ~250 samples across 33 CC mouse… | ||
| Exponentiating Single-Cell Sequencing | Jimmie Ye | 35m |
Generates a comprehensive single-cell lung atlas and pairs it with transcriptome-wide spatial profiling using Nanostring WTA of post-mortem COVID-19 lungs to… | ||
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