Dan Ofer
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View article: Protein Language Models Expose Viral Immune Mimicry
Protein Language Models Expose Viral Immune Mimicry Open
Viruses have evolved sophisticated solutions to evade host immunity. One of the most pervasive strategies is molecular mimicry, whereby viruses imitate the molecular and biophysical features of their hosts. This mimicry poses significant c…
View article: Short-Term Prediction Model for Breast Cancer Risk Based on One Million Medical Records
Short-Term Prediction Model for Breast Cancer Risk Based on One Million Medical Records Open
Use of data readily available from the EMR, can assist clinicians when assessing the short-term breast cancer risk.
View article: InterFeat: A Pipeline for Finding Interesting Scientific Features
InterFeat: A Pipeline for Finding Interesting Scientific Features Open
Finding interesting phenomena is the core of scientific discovery, but it is a manual, ill-defined concept. We present an integrative pipeline for automating the discovery of interesting simple hypotheses (feature-target relations with eff…
View article: Protein Language Models Expose Viral Mimicry and Immune Escape
Protein Language Models Expose Viral Mimicry and Immune Escape Open
Motivation Viruses elude the immune system through molecular mimicry, adopting biophysical characteristics of their host. We adapt protein language models (PLMs) to differentiate between human and viral proteins. Understanding where the im…
View article: Detecting anomalous proteins using deep representations
Detecting anomalous proteins using deep representations Open
Many advances in biomedicine can be attributed to identifying unusual proteins and genes. Many of these proteins’ unique properties were discovered by manual inspection, which is becoming infeasible at the scale of modern protein datasets.…
View article: ProteinBERT Trained model
ProteinBERT Trained model Open
Trained ProteinBERT model weights for the paper "ProteinBERT: A universal deep-learning model of protein sequence and function". https://github.com/nadavbra/protein_bert Also available via FTP: ftp://ftp.cs.huji.ac.il/users/nadavb/protein_…
View article: Automated Annotation of Disease Subtypes
Automated Annotation of Disease Subtypes Open
Background Distinguishing diseases into distinct subtypes is crucial for study and effective treatment strategies. The Open Targets Platform (OT) integrates biomedical, genetic, and biochemical datasets to empower disease ontologies, class…
View article: Whats next? Forecasting scientific research trends
Whats next? Forecasting scientific research trends Open
Scientific research trends and interests evolve over time. The ability to identify and forecast these trends is vital for educational institutions, practitioners, investors, and funding organizations. In this study, we predict future trend…
View article: Detecting Anomalous Proteins Using Deep Representations
Detecting Anomalous Proteins Using Deep Representations Open
Many advances in biomedicine can be attributed to identifying unusual proteins and genes. Many of these proteins’ unique properties were discovered by manual inspection, which is becoming infeasible at the scale of modern protein datasets.…
View article: Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game
Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game Open
Humor is an inherently social phenomenon, with humorous utterances shaped by what is socially and culturally accepted. Understanding humor is an important NLP challenge, with many applications to human-computer interactions. In this work w…
View article: Inferring microRNA regulation: A proteome perspective
Inferring microRNA regulation: A proteome perspective Open
Post-transcriptional regulation in multicellular organisms is mediated by microRNAs. However, the principles that determine if a gene is regulated by miRNAs are poorly understood. Previous works focused mostly on miRNA seed matches and oth…
View article: Revisiting the Risk Factors for Endometriosis: A Machine Learning Approach
Revisiting the Risk Factors for Endometriosis: A Machine Learning Approach Open
Endometriosis is a condition characterized by implants of endometrial tissues into extrauterine sites, mostly within the pelvic peritoneum. The prevalence of endometriosis is under-diagnosed and is estimated to account for 5–10% of all wom…
View article: Inferring microRNA regulation: A proteome perspective
Inferring microRNA regulation: A proteome perspective Open
Post-transcriptional regulation in multicellular organisms is mediated by microRNAs. However, the mechanisms that determine if a gene is regulated by miRNAs are poorly understood. Previous works focused mostly on miRNA seed matches and oth…
View article: Unified Predictive Model for Endometriosis: Merging Clinical, Self-reporting and Genetic Information
Unified Predictive Model for Endometriosis: Merging Clinical, Self-reporting and Genetic Information Open
Endometriosis is a condition characterized by implants of endometrial tissues into extrauterine sites, mostly within the pelvic peritoneum. The prevalence of endometriosis is under-diagnosed, and estimated to account for 5–10% of all women…
View article: ProteinBERT: a universal deep-learning model of protein sequence and function
ProteinBERT: a universal deep-learning model of protein sequence and function Open
Summary Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optim…
View article: Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game
Cards Against AI: Predicting Humor in a Fill-in-the-blank Party Game Open
Humor is an inherently social phenomenon, with humorous utterances shaped by what is socially and culturally accepted. Understanding humor is an important NLP challenge, with many applications to human-computer interactions. In this work w…
View article: ProteinBERT: A universal deep-learning model of protein sequence and function
ProteinBERT: A universal deep-learning model of protein sequence and function Open
Self-supervised deep language modeling has shown unprecedented success across natural language tasks, and has recently been repurposed to biological sequences. However, existing models and pretraining methods are designed and optimized for…
View article: ICU Survival Prediction Incorporating Test-Time Augmentation to Improve the Accuracy of Ensemble-Based Models
ICU Survival Prediction Incorporating Test-Time Augmentation to Improve the Accuracy of Ensemble-Based Models Open
This work presents a novel method for applying test-time augmentation (TTA) to tabular data. We used TTA along with an ensemble of 42 models to achieve higher performance on the MIT Global Open Source Severity of Illness Score dataset cons…
View article: Reduced Mortality During Holidays and the COVID-19 Pandemic in Israel
Reduced Mortality During Holidays and the COVID-19 Pandemic in Israel Open
Evidence suggests varied trends in mortality surrounding the holiday period. Most studies support an association between increased mortality rates and holidays. We compare the effect of the number of holiday days per week on the overall mo…
View article: Overlooked Short Toxin-Like Proteins: A Shortcut to Drug Design
Overlooked Short Toxin-Like Proteins: A Shortcut to Drug Design Open
Short stable peptides have huge potential for novel therapies and biosimilars. Cysteine-rich short proteins are characterized by multiple disulfide bridges in a compact structure. Many of these metazoan proteins are processed, folded, and …
View article: Machine Learning for Protein Function
Machine Learning for Protein Function Open
Systematic identification of protein function is a key problem in current biology. Most traditional methods fail to identify functionally equivalent proteins if they lack similar sequences, structural data or extensive manual annotations. …
View article: ASAP: a machine learning framework for local protein properties
ASAP: a machine learning framework for local protein properties Open
Determining residue-level protein properties, such as sites of post-translational modifications (PTMs), is vital to understanding protein function. Experimental methods are costly and time-consuming, while traditional rule-based computatio…
View article: Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy Open
A document containing a subset of CAFA2 analyses that are equivalent to those provided about the CAFA1 experiment in the CAFA1 supplement. (PDF 11100 kb)