Founded in 1920, the NBER is a private, non-profit, non-partisan organization dedicated to conducting economic research and to disseminating research findings among academics, public policy makers, an...

The Faculty of Arts and Sciences slashed the number of Ph.D. student admissions slots for the Science division by more than 75 percent and for the Arts & Humanities division by about 60 percent for th...

Studies of rodents with a menstrual on/off switch could help people with endometriosis and other disorders

A newly designated butterfly species, Euptychia andrewberryi, has been named in honor of Harvard lecturer Andrew J. Berry by postdoctoral fellow Shinichi Nakahara, who identified the species.

During menstruation, an inner layer of the endometrium is selectively shed, while an outer, progenitor-containing layer is preserved to support repeated regeneration. Progress in understanding this co...

World Ice Theory and the supernatural imaginary of the Third Reich.

In addition to messenger RNA (mRNA) that provide the code for proteins, there are other RNAs that exert their function just as RNA, usually referred to as non-coding […]

Structural RNAs exhibit a vast array of recurrent short three-dimensional (3D) elements found in loop regions involving non-Watson–Crick interactions that help arrange canonical double helices into tertiary structures. Here we present CaCoFold-R3D, a probabilistic grammar that predicts these RNA 3D motifs (also termed modules) jointly with RNA secondary structure over a sequence or alignment. CaCoFold-R3D uses evolutionary information present in an RNA alignment to reliably identify canonical helices (including pseudoknots) by covariation. Here we further introduce the R3D grammars, which also exploit helix covariation that constrains the positioning of the mostly noncovarying RNA 3D motifs. Our method runs predictions over an almost-exhaustive list of over 50 known RNA motifs (‘everything’). Motifs can appear in any nonhelical loop region (including three-way, four-way and higher junctions) (‘everywhere’). All structural motifs as well as the canonical helices are arranged into one single structure predicted by one single joint probabilistic grammar (‘all-at-once’). Our results demonstrate that CaCoFold-R3D is a valid alternative for predicting the all-residue interactions present in a RNA 3D structure. CaCoFold-R3D is fast and easily customizable for novel motif discovery and shows promising value both as a strong input for deep learning approaches to all-atom structure prediction as well as toward guiding RNA design as drug targets for therapeutic small molecules.

President Donald Trump told reporters on Tuesday in the Oval Office that the White House had “reached a deal” with Harvard, before cautioning that the agreement had not been finalized.