Bioinformatics resources and tools, consultation, training, and services offered by the Medical Library are free for any Yale affiliate including faculty, students, postdocs, and staff.
Consultation is available (free of charge) to individuals, groups or team to address bioinformatics-related research questions and needs. Consultation is mainly provided in-person but less complex questions may be addressed over email or by phone. Contact Rolando Milian to schedule a consultation service: 203-785-6194 or email@example.com.
Examples of consultation topics are:
- Analysis of microarray and next-generation sequencing (NGS) data using library-licensed bioinformatics tools
- Enrichment (pathway and network) analysis of differentially regulated molecules.
- Finding, retrieving, and using public datasets for cross-referencing research results or hypothesis testing
- Complex literature searches.
- Identification of appropriate bioinformatics software or databases to answer specific research questions
- Development or narrowing hypothesis in silico by using existing public omics data and literature
- Hands-on tutorials on bioinformatics software licensed by the Medical Library
The Yale Cushing/Whitney Medical Library Bioinformatics End User Support Program provides letters of support for grant applications. In addition, it offers collaborative data analysis services (co-authorship) for complex high-throughput data analysis projects.
The CWML End User Bioinformatics Support license a variety of commercial bioinformatics software in support of the biomedical research data lifecycle. These tools are free of charge to Yale biomedical researchers (including students, postdocs, and staff). Click on each link below to request/register for an account. Contact Rolando Milian (203-785-6194 - firstname.lastname@example.org) or Lindsay Barnett (203-785-2883 email@example.com) for questions or comment on these programs.
Ingenuity Pathway Analysis (IPA)
This is a manually-curated knowledge base obtained from the peer-reviewed biomedical literature, public and private databases. With IPA, you can identify relevant biomarkers, contextualize metabolomics, proteomics, toxicogenomics, and transcriptomics data, and perform pathway network analysis among others. Register OR Login to IPA
MetaCore/MetaDrug (Clarivate Analytics)
MetaCore is an online software based on manually-curated knowledgebase of transcription factors, receptor/ligands, kinase, drugs from the biomedical literature. MetaCore can be used for the functional analysis of the NextGen sequence data, CNV, microarray, proteomics, metabolic, SAGE, proteomics, siRNA, microRNA, and screening data. MetaDrug contains curated information on biological effects of small molecule compounds. It is a systems pharmacology solution that combines pharmacogenomics and toxicogenomics as well as predictive capabilities. Register OR Login to MetaCore
Integrity Clarivate Analytics)
Integrity focuses exclusively on pharma and drug development intelligence, harmonizing and integrating essential biological, chemical, and pharmacological data from disparate sources into a single platform. Integrity provides easy access to pipeline data, granular target and MOA information, and manually curated data specific to drug development. Request an account by filling this form OR Login to Integrity
This software is used for the analysis of next generation sequencing data including RNA, small RNA, and DNA sequencing. It has a user-friendly graphical interface that allows to build your own custom analysis pipelines for Alignment, Quantification, Quality control, Statistics, and Visualization Register OR Login to Partek Flow
Knowledge Library (TRANSFAC)
The BIOBASE Knowledge Library™ (BKL) is a collection of gene-regulation and protein oriented scientific databases created from the peer-reviewed scientific literature. The TRANSFAC®, and PROTEOME™ products are included in BIOBASE. Visit
Ingenuity Variant Analysis
You can identify variants and verify them. Find disease-causing variants faster by using 16+ years of expert manual curation of the scientific literature. By indexing all known disease-causing biological processes, it can deliver new insights and increased likelihood of homing in on the causal variant you’re seeking. Register OR Login to IVA
BioCyc is a genome and metabolic pathway web portal covering more than 5,500 organisms. It enables visualization of metabolomics data on individual pathway diagrams and on the organism-specific metabolic map diagrams that are available for every BioCyc organism. In addition, it has online tools for browsing metabolic/regulatory networks, gene, metabolites within the networks, examine the connectivity of the network, and other functionalities. Visit
Qlucore Omics Explorer
This resource facilitates a dynamic, visualization-guided analysis of OMICs data, applicable to various phases of a discovery cycle. With Qlucore, you can visualize, perform quality control, apply statistics, perform 3D principal component analysis, and create publication-ready graphics, heat maps, and various 2D plots. GSEA and GO are available for biological exploration. Use valuable public data (TCGA, GEO) to test your ideas, or generate/narrow new hypotheses, with an easy download and integration into your data analysis. Register
The Bioinformatics Support Program offers wide variety of bioinformatics training, presentations and demos for any Yale affiliate including students, postdocs, and staff. Training is free but registration is required due to limited seating.
Check the Calendar for upcoming bioinformatics events.
- Charkoftaki G, Thompson DC, Golla JP, Garcia-Milian R, Lam TT, Engel J, Vasiliou V. Integrated multi-omics approach reveals a role of ALDH1A1 in lipid metabolism in human colon cancer cells.Chem Biol Interact. 2019 Mar 6. pii: S0009-2797(18)31314-0. doi: 10.1016/j.cbi.2019.02.030 https://www.ncbi.nlm.nih.gov/pubmed/30851239
- Chen Y, Golla S, Garcia-Milian R, Thompson D, Gonzalez FJ, Vasiliou V. Hepatic metabolic adaptation in a murine model of glutathione deficiency. Chemo-Biological Interactions (2019) https://doi.org/10.1016/j.cbi.2019.02.015
Mis M, Yang Y, Tanaka B, Gomis-Perez C, Liu S, Dib-Hajj F, Adi T, Garcia-Milian R, Schulman B, Dib-Hajj D, Waxman S. Resilience to Pain: A Peripheral Component Identified using induced Pluripotent Stem Cells. The Journal of Neuroscience. (2018) doi: 10.1523/JNEUROSCI.2433-18. https://www.ncbi.nlm.nih.gov/
Perkins AN, Inayat-Hussain SH, Deziel NC, Johnson CH, Ferguson SS, Boyles AL, Garcia-Milian R, Thompson DC, Vasiliou V. Evaluation of Potential Carcinogenicity of Organic Chemicals in Synthetic Turf Crumb Rubber Environmental Research, Elsevier, October 2018 https://doi.org/10.1016/j.
envres.2018.10.018 https://www.ncbi.nlm.nih.gov/ pubmed/30458352
Inayat-Hussain S, Aziz AM, Fukumura M, Chai MJ, Deziel N, Garcia-Milian R, Vasiliou V, Low WJ. Prioritization of Reproductive Toxicants in Unconventional Oil and Gas Operations Using a Multi-Country Regulatory Data-Driven Hazard Assessment. Environment International 117:348-358, 2018 doi: 10.1016/j.envint.2018.05.010 https://www.ncbi.nlm.nih.gov/
Garcia-Milian R, Hersey D, Vukmirovic M, Duprilot F. (2018) Data challenges of biomedical researchers in the age of omics. PeerJ 6:e5553 https://www.ncbi.nlm.nih.gov/
Pelekanou V, Anastasiou E, Bakogeorgou E, Notas G, Kampa M, Garcia-Milian R, Lavredaki K, Moustou E. Estrogen receptor-alpha isoforms are the main estrogen receptors expressed in Non-Small Cell Lung Carcinoma. Steroids (Elsevier) 2018 pii: S0039-128X(18)30016-3. doi: 10.1016/j.steroids.2018.01.008 https://www.ncbi.nlm.nih.gov/
Guo X, Qiu W, Garcia-Milian R, Lin X, Zhang Y, Cao Y, Tan Y, Wang Z, Shi J, Wang J, Liu D, Song L, Xu Y, Wang X, Liu Na, Sun T, Zheng J, Luo J, Zhang H, Xu J, Kang L, Ma C, Wang K, Luo X. Genome-wide significant, replicated and functional risk variants for Alzheimer’s disease Journal of Neural Transmission p1-17, 2017 https://doi.org/10.1007/
s00702-017-1773-0 https://www.ncbi.nlm.nih.gov/ pubmed/28770390
Zuo L, Garcia-Milian R, Guo X, Zhong C, Tan Y, Wang Z, Wang J, Chiang-Shan Li, Luo X. Replicable risk nicotinic cholinergic receptor genes for nicotine dependence. Genes 7(11), 95 doi:10.3390/genes7110095, 2016 http://www.mdpi.com/2073-4425/
7/11/95 https://www.ncbi.nlm.nih.gov/ pubmed/27827986