Blogs

Librarians at Yale have developed numerous online guides for Yale users.  Here at Yale, our guides can provide a number of things, including: Research guidance for a particular Yale course; Instructions on how to research a subject; Documentation for a research tool or service; or Instructions on accessing and using collections or resources. You might find different guides of particular interest based on your role and field, for example: NIH Public Access Policy, for researchers who receive NIH funding and the staff who support them. Get started exploring our full list of guides in the field of medicine, or browse all Yale guides including on topics outside the health sciences. 

(by Nathan Rupp and Melissa Grafe) Nearly 900 Yale School of Medicine theses are now available through Yale University’s online institutional repository known as EliScholar. These include “current” theses published in the last decade that have come out of embargo as well as several YSM alumni theses published as far back as 1952. These theses document the rich research done by Yale’s medical students, and can provide a starting point for current medical students embarking on their projects.  We’re also pleased to make this part of our collection more openly accessible to researchers in general, as the print theses are stored in locked stacks at the Medical Library.  Current YSM students can browse this collection for examples of what a YSM thesis looks like. For more information about accessing theses at the Medical Library, please see https://library.medicine.yale.edu/collections/thesis.

Monica Green, a scholar of the history of medieval medicine, recently profiled the Bamberg Surgery, which is part of the Medical Historical Library's collection.  The Bamberg Surgery is a surgical text dating from the mid-12th century which was acquired by Dr. Harvey Cushing and subsequently formed part of the original Medical Historical collection at Yale.  Green writes: The Bamberg Surgery doesn’t get a lot of love in histories of surgery, because of its patchwork character. As Corner himself said, “it is a notebook, a partially organized collection of notes, memoranda, prescriptions, and excerpts from other books.” But the Bamberg Surgery merits a closer look to contemplate the question with which we began: how do you begin to build up a body of written surgical knowledge when previously you had none? The Bamberg Surgery draws selectively from the (now complete) translation of (Persian physician​‘Ali ibn al-‘Abbas) al-Majusi’s text, which it fuses with an early medieval text on phlebotomy that circulated under Hippocrates’ name. It then expands on these elements with new pharmaceuticals, new techniques, and elements of anatomical and physiological learning drawn from other texts. For example, al-Majusi’s text had never mentioned marciaton, a compound medicine for a wax-based unguent passed on through the early medieval Latin pharmaceutical tradition. The Chirurgia salernitana had recommended its use, and we find it in the Bamberg Surgery likewise, being recommended for nerve damage from a wound, broken bones, and dislocations. Similarly, the author cites Galen’s Tegni several times, a translation of the foundational handbook of medicine composed by the 2nd-century Greek polymath, used widely in the Islamic world and, increasingly, in Europe as a basic introduction to medical theory and practice.    

The Yale Medical Library is providing to all Yale affiliates free access to two of the most powerful commercial bioinformatics tools for the analysis of omics data: MetaCore and Ingenuity Pathway Analysis. This is part of a pilot project conducted by the medical library in order to find sustainable and long term access to these tools. Please register for these upcoming trainings if you are interested in learning how to use these tools or if you need a refresher. For questions on how to register for an account or comments please contact Rolando Milian Title: Introduction to Ingenuity Pathway Analysis Description: What is IPA and what questions can it address? Overview of key features in IPA Ingenuity Knowledge Base Search & Pathway Building - Gene/ Chemical, Functions, Drug Targets Advanced Search: Limiting results to a molecule type, family or disease-association. Building pathways: Creating a pathway, pathway navigating, Using Build and Overlay tools Bioprofiler Dataset Analysis: Interpretation of Gene, Transcript, Protein and Metabolite Data Data Upload and Analysis:  Uploading and formatting a dataset, setting analysis parameters and running an analysis Pathway Analysis and Canonical Pathways Downstream Effects Analysis and identifying downstream functions and processes that are likely affected Upstream regulators Analysis Causal Network Analysis and identifying likely root regulators Regulator Effects Analysis to link upstream regulators with downstream functions and processes that are affected Comparison analysis and comparing multiple observations Date & Time:      9:00am - 12:00pm, Tuesday, October 27, 2015 Location:              H-203, Jane Ellen Hope Building, 315 Cedar St, New Haven CT Presenter:          Field Scientist QIAGEN Informatics   Title:      MetaCore: Getting the most from your "omics" analysis (Introductory session) Description: The ability to generate massive amounts of data with "omics" analysis begs the need for a tool to analyze and prioritize the biological relevance of this information. GeneGo provides a solution for using "omics" gene lists to generate and prioritize hypotheses with MetaCore. This tutorial highlights how to work with different types of data (genomics, proteomics, metabolomics and interaction data) beginning with how to upload gene lists and expression data (if available). Here we demonstrate data manager capabilities including how to upload, batch upload, store, share and check data properties and signal distribution. We then focus on how MetaCore uses your gene list to extract functional relevance by determining the most enriched processes across several ontologies. This entails a detailed lesson on how to prioritize your hypothesis using the statistically significance enrichment histograms and associate highly interactive GeneGo Maps and pre-built networks. We further emphasize the role of expression data in your analysis and the ability to visually predict experimental results, associated disease and possible drug targets. Lastly we highlight the benefits of using MetaCore workflows to compare data sets and work with experiment intersections. Date & Time:      10:00am - 12:00pm, Tuesday, November 3, 2015 Location:              C-103 - SHM 333 Cedar St, New Haven CT 06520 Presenter:          Dr. Matthew Wampole, Solution Scientist, IP & Science, Thomson Reuters   Title:      MetaCore: Getting the most from your "omics" analysis (Advanced) Description: In the advanced tutorial, we will explore uses of our network building algorithms and methods for hypothesizing key hubs passed on data. We will begin this session with a discussion on using the Key Pathway Advisor to hypothesize key hubs regulating gene expression data. The session will then review ways of using the 11 network building algorithms in MetaCore. The first example will review how to build a network purely from the curated knowledge within MetaCore. Then we will go through an example of using omics data to build a network of interactions to better understand the relationships within our data. Date & Time:      1:00pm - 3:00pm, Tuesday, November 3, 2015 Location:              C-103 - SHM 333 Cedar St, New Haven CT 06520 Presenter:          Dr. Matthew Wampole, Solution Scientist, IP & Science, Thomson Reuters     Join the End-user Bioinformatics Group and become a member of a community that collaborates on end-user bioinformatics events, training sessions, resources, and tools that support biomedical research at Yale.

The National Center for Biotechnology Information is developing a new type of BLAST called SmartBLAST. It process the user query in such a way that presents the three best matches from the non-redundant protein sequence database along with the two best protein matches from well-studied reference species. In addition, it provides results that match the query from the Conserved Domain Database (CDD) SmartBLAST accepts only one query at a time- either as FASTA sequence or protein accession number/GI- and uses a combination of BLAST and a multiple sequence alignment to produce its results. It first uses the query to search the non-redundant (nr) protein database. Then, it searches the reference database with BLASTP, followed by a multiple sequence alignment on the six sequences (the query and five subject sequences) using the COBALT multiple sequence alignment program. Screen capture showing the results of a SmartBLAST for TP53 (GI:187830777). Panel A shows the five matching sequences are represented as a phylogenetic tree and a graphical overview. The matches are color-coded: matches from the reference species are green, matches from the non-redundant protein database are blue, and your query is yellow. Panel B represents the results from the multiple alignments. Join the End-User Bioinformatics Network (EBNET) and become a member of a grass root community that collaborates on end-user bioinformatics events, training sessions, resources, and tools that support biomedical research at Yale.