Abstract

Academic writing is one of the most valuable skills a scientist can develop. A primary challenge for graduate students is to coherently and concisely organize and present ideas within a manuscript. Writing a quality research manuscript requires transmitting the most relevant information through precise sentences that fulfill diverse communicational roles, ultimately resulting in a coherent, understandable text connected by cohesive mechanisms (e.g. lexical relationships between pairs of terms). Despite technological advances, the execution and teaching of the writing process have not similarly advanced. Therefore, a top priority for graduate programs is to implement new methodologies and technologies that aid students in communicating research advances. Through our investigation, we developed a novel, unsupervised machine-learning model applied to cell biology and biomedical texts that guides students in writing better organized and more structured texts