Yedael Y. Waldman

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Synonymous mutations do not alter the protein produced yet can have a significant effect on protein levels. The mechanisms by which this effect is achieved are controversial; although some previous studies have suggested that codon bias is the most important determinant of translation efficiency, a recent study suggested that mRNA folding at the beginning(More)
The prioritization of candidate disease-causing genes is a fundamental challenge in the post-genomic era. Current state of the art methods exploit a protein-protein interaction (PPI) network for this task. They are based on the observation that genes causing phenotypically-similar diseases tend to lie close to one another in a PPI network. However, to date,(More)
Synthetic lethality occurs when the inhibition of two genes is lethal while the inhibition of each single gene is not. It can be harnessed to selectively treat cancer by identifying inactive genes in a given cancer and targeting their synthetic lethal (SL) partners. We present a data-driven computational pipeline for the genome-wide identification of SL(More)
Various studies in unicellular and multicellular organisms have shown that codon bias plays a significant role in translation efficiency (TE) by co-adaptation to the tRNA pool. Yet, in humans and other mammals the role of codon bias is still an open question, with contradictory results from different studies. Here we address this question, performing a(More)
Many complex human diseases are highly sexually dimorphic, suggesting a potential contribution of the X chromosome to disease risk. However, the X chromosome has been neglected or incorrectly analyzed in most genome-wide association studies (GWAS). We present tailored analytical methods and software that facilitate X-wide association studies (XWAS), which(More)
Utilizing molecular data to derive functional physiological models tailored for specific cancer cells can facilitate the use of individually tailored therapies. To this end we present an approach termed PRIME for generating cell-specific genome-scale metabolic models (GSMMs) based on molecular and phenotypic data. We build >280 models of normal and cancer(More)
The tumor suppressor gene TP53 is known to be a key regulator in cancer, and more than half of human cancers exhibit mutations in this gene. Recent evidence shows that point mutations in TP53 not only disrupt its function but also possess gain-of-function and dominant-negative effects on wild-type copies, thus making the mutated gene an oncogene. Hence,(More)
Synonymous mutations are considered to be "silent" as they do not affect protein sequence. However, different silent codons have different translation efficiency (TE), which raises the question to what extent such mutations are really neutral. We perform the first genome-wide study of natural selection operating on TE in recent human evolution, surveying(More)
Numerous metabolic alterations are associated with the impairment of brain cells in Alzheimer's disease (AD). Here we use gene expression microarrays of both whole hippocampus tissue and hippocampal neurons of AD patients to investigate the ability of metabolic gene expression to predict AD progression and its cognitive decline. We find that the prediction(More)
The Bene Israel Jewish community from West India is a unique population whose history before the 18th century remains largely unknown. Bene Israel members consider themselves as descendants of Jews, yet the identity of Jewish ancestors and their arrival time to India are unknown, with speculations on arrival time varying between the 8th century BCE and the(More)