SciReader for Scientific and Health Literacy
Projects
News
Teaching
Funding
Employment
The Bio-toolkit software collection (icons above)
C-Terminome - for examining the function of the C-terminus of proteins
HIVtoolbox - for investigating HIV virology and discovery of new drug targets
Minimotif Miner - minimotif prediction of new functions in proteins and disease
VENN - plots sequence conservation onto protein structures
SciReader - for reading complex scientific and medical documents
GoMAP - geogenomic mutational atlas of resistance
MimoSA - a downloadable app for annotating the primary literature
JImpactFactor helps scientists choose where to publish their papers
Minimotif Miner Query Engine for building consensus minimotifs and PSSMs
Marty's Links - a collection of weblinks useful for scientists
JBOG - identifies all proteins in a proteome having the same predicted molecular mass

We ask you to cite our applications whenever they are used for research that results in a publication or if a figure is made using one of our applications. This helps us support and create new version with more capabilities.

Schiller Lab and Bio-tookit links

only search Bio-toolkit.com
Relevant links
Collaborators
HIV Ontology at BioPortal
MnM at Wikipedia
MnM at NAR Molecular Biology Database Collection
HIVToolbox at Wikipedia
Short Linear Motifs at Wikipedia
_________________________________________________________________________________________________
GoMap
We present a new approach for pathogen surveillance we call Geogenomics. Geogenomics examines the geographic distribution of the genomes of pathogens, with a particular emphasis on those mutations that give rise to drug resistance. We engineered a new web tool called Geogenomic Mutational Atlas of Pathogens (GoMAP) that enables investigation of the global distribution of individual drug resistance mutations. As a test case we examined mutations associated with HIV resistance to FDA-approved antiretroviral drugs. Approximately 40 million people are infected with HIV and one of the major limitations in HIV drug therapy is loss of effectiveness due to HIV acquiring or transmitting drug resistance mutations. The GoMAP-HIV makes use of existing public drug resistance and HIV protein sequence data to examine the distribution of 872 drug resistance mutations in ~502,000 sequences for many countries in the world. GoMAP also uses a broadened classification scheme for HIV drug resistance mutations. GoMAP-HIV is an open access web application available at gomap.bio-toolkit.com/GoMap/. GoMap was built by David Sargeant, Michael Hedden, and Sandeep Deverasetty, with contributions from Steve Schooler, Dr. Christy Strong, and ~25 undergraduate students in the Schiller lab

PLEASE CITE USE OF GoMap WITH THIS PAPER:
Sargeant DP et. al. (2014)The Geogenomic Mutational Atlas of Pathogens (GoMAP) Web System. PLoS One 9:e92877 PMID: 24675726
_________________________________________________________________________________________________
C-terminome
The C-termini are often very important for protein function, containing short contiguous peptide sequences (minimotifs) that encode post-translational modification, zipcode minimotifs for trafficking proteins to specific cell compartments, and establish binding to other proteins and molecules. Through our annotation of 100,000s of minimotifs in the Minimotif Miner database our lab has catalogued >1000 known functional minimotifs specific to the carboxy (C)-termini of proteins. Some types of functions are found in a limited set of proteins such as the SKL> minimotif for import of proteins into peroxisomes. This is a searchable interface for a human database of minimotif patterns and functions of the carboxy-termini of all human proteins. The C-terminome website was built by Michael Hedden and Oniel Toledo. This is currently a beta version.
_________________________________________________________________________________________________
HIVtoolbox2
The goal of this project is to create an integrated webtool that can be used to investigate potential drug targets in HIV. HIVtoolbox2 is an analytic tool that integrates data for all HIV proteins. The application has a sequence window that maps domains, functional sites, protein-protein interactions, and potential functional minimotifs to the sequence (Sargeant et al., 2014 pending, (Sargeant et al, 2008). The sequence is coupled to six interactive structure viewers that are synchronized. These structure windows show structures colored by domains, predicted minimotifs, functional sites, protein-protein interactions, sequence conservation, drug resistance mutations, drug binding sites, and immune eptipopes. Sequence conservation is calculated for many thousand different sequences from isolates. This is integrated with a species/group/clade selected and sequence alignment/PSSM display. HIVtoolbox was built by David Sargeant, Sandeep Deverasetty, Angel Villahoz Baleta, and Mike Hedden. Relevant links: Wikipedia article; IAS 2012 meeting presentation; HIVToolbox2 user guide; HIVToolbox2 video tutorials. The original version of HIVToolbox v1.0, a HIVToolbox v1.0 User Guide, and HIVToolbox v1.0 Video tutorials are still available, but no longer maintained.

PLEASE CITE USE OF HIVTOOLBOX WITH THIS PAPER:
David P. Sargeant, et al. (2014) The HIVToobox 2 web system integrates sequence, structure, function and mutation analysis. PLoS One, 9, e98810. PMID: 24886930

Sargeant D, Deverasetty S, Luo Y, Baleta AV, Zobrist S, Rathnayake V, Russo JC, Vyas J, Muesing MA, and Schiller MR (2011) HIVToolbox, an integrated web application for investigating HIV. PLoS One, 6, e20122. PMID: 21647445
_________________________________________________________________________________________________
Minimotif Miner
Developing protein-protein interaction theory is important for our understanding of the cell, disease mechanisms, and to facilitate drug design. The theory behind protein-protein interactions is based on first principle theory of molecular interactions and the identification of a rapidly growing number of short peptide motifs (less than 15 amino acids) that can bind to, or be acted upon by protein domains. Other than those interactions mediated through short motifs we have virtually no ability to predict protein-protein interactions.

My lab is continuing annotation of Minimotif Miner, the first bioinformatics tool that is a comprehensive database of short functional motifs currently containing ~300,000 unique motifs (Mi et al., 2012, Rajasekaran et al, 2009 , Balla et al, 2006, ). Minimotif Miner can be used by any scientist to generate new hypotheses about the function of any protein and postulate mechanisms by which mutations cause any human disease. Current projects are aimed at completing this database and studing the roles of minimotifs in biology. We recently reported and implemented an algorithm that drastically increases the accuracy of minimotif predictions; upto 90% accuracy (Mi et al., 2012). We also have now shown that structure is an important determinant of miniimotifs and have helped advanced a better theoretical undestanding of false positive predcitions (Sargeant et al., 2012). Minimotif Miner was built in collaboration with several scientists at the University of Nevada, LAS VEgas, University of Connecticut and its Health Center. See more on Minimotif Miner at [wikipedia]

PLEASE CITE USE OF MINIMOTIF MINER WITH THESE PAPERS:
Balla S, Thapar V, Verma S, Luong T, Faghri T, Huang C-H, Rajasekaran S, del Campo JJ, Shinn JH, Mohler WA, Maciejewski MW, Gryk MR, Piccirillo B, Schiller SR, and Schiller MR. (2006). Minimotif Miner, a tool for investigating protein function.. Nat. Methods, 3, 175-177. PMID: 16489333

Rajasekaran S, Balla S, Gradie P, Gryk MR, Kadaveru K, Kundeti V, Maciejewski MW, Mi T, Rubino N, Vyas J, Schiller MR. (2009). Minimotif Miner 2nd release: a database and web system for motif search. Nucleic. Acids Res., 37, D185-190.
PMID: 18978024, PMCID: PMC2686579

Mi T, Merlin JC, Deverasetty S, Gryk MR, Bill TJ, Brooks AW, Lee LY, Rathnayake V, Ross CA, Sargeant DP, Strong CL, Watts P, Rajasekaran S, Schiller MR (2012). Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences. Nucleic Acids Res., 40 (database issue), D252-260.
PMID: 22146221, PMCID: PMC3245078
_________________________________________________________________________________________________
Venn
VENN is an integrative computer program, written by Jay Vyas, for mapping protein sequence conservation among homologues onto a three dimensional structure of a protein (Vyas et al., 2009). VENN was named after John VENN, the inventor of VENN diagrams, because VENN can be used to explore the interaction of sequence and structure to identify important functional regions in proteins, The only input needed in a VENN analysis is an experimental or model PDB structure identifier (e.g. 1EX4). An alternative site for structure models can be found here . VENN retrieves and interprets the PDB file to identify different structure chains. Protein sequences with sequence similarity to each chain are automatically retrieved from the EBI and a list of up to 500 such sequences is presented to the user. The user selects sequences using canned strategies or by their own ad hoc selections. VENN then aligns the protein sequences, calculates a heatmap for conservation of each amino acid position and plots the heatmap onto the protein structure. Different strategies for selecting groups of sequences can be used to identify functional regions and specificity determinants in gene families.

Do to changes in the data access at EBI, the stand alone version of VENN no longer functions and has been deprecated. This has been replaced by a web version of VENN that contains all of the critical functions reported in the publication. VENN was built by Jay Vyas.

PLEASE CITE USE OF VENN WITH THIS PAPER:
Vyas J, Gryk MR, and Schiller. (2009). Venn, a tool for titrating sequence conservation onto protein structures. Nucleic Acids Res., 37, e124. PMID: 19656955
_________________________________________________________________________________________________
XReader (formerly SciReader)

Launch XReader now!

XReader, formerly called Scireader, is a web and mobile application where a document can be uploaded and mapped to nearly 1,000,000 biological and English word definitions. A small frame in the top of the window displays any word selected from an uploaded document. No more changing pages to figure out the meaning of that biological or medical word. Mobile app expected release date is February 2013

Interested in XReader? Sign up for news and updates!

XReader links:
        



PLEASE CITE USE OF XREADER: Gradie PR, Litster M, Thomas R, Vyas J, Schiller MR. (2011). SciReader enables reading of medical content with instantaneous definitions. BMC Med Inform Decis Mak, 11, 4. PMID: 21266060
_________________________________________________________________________________________________
JBOG
JBOG (Java-based Band On Gel) can be used to identify all proteins in a proteome in a small range of molecular masses. Did you ever run a gel and wonder what might be in that band? JBOG can provide you with a list of potential answers. JBOG was written by Jay Vyas.
_________________________________________________________________________________________________
Axonal Outgrowth
Understanding how neurons initiate axon outgrowth is important, not just for our basic understanding of neuronal connectivity, but also for treating neurodegenerative diseases, spinal cord injury, and head trauma. Axonal outgrowth requires the coordination of many cellular processes. As the axon navigates the nervous system to find targets, it must make complicated decisions that require a higher level of interpretation. Very little is known how the axon is capable of interpreting the many inputs it receives. to address this question, we are continuing to study how a multidomain protein called Kalirin is involved in coordination of axonal signal processing (May et al., 2001, Penzes et al, 2003, Schiller et al. 2005, Schiller et al. 2006, Chakrabarti et al. 2006, Schiller, 2007, Schiller et al. 2008, Gorbatyuk et al., 2012). This project has involved the determination of structures for two domains of Kalirin (2KR9, 1U3O), which has given insight into its mechanism of action Schiller et al. 2006.
_________________________________________________________________________________________________
JImpactFactor
JImpactFactor uses keywords and authors to find the most relevant place to publish your scientific work. JImpactFactor is based on the TextMine algorithm (Vyas et al., 2009, A Proposed Syntax for Minimotif Semantics, Version 1. BMC Genomics., 10, 360. PMID: 19656396.
_________________________________________________________________________________________________
Marty's Weblinks
This is a collection of weblinks useful for biologists. This include weblinks to NCBI databases, medical dictionary, statistical analysis packages, genetic code, rodent atlases, funding sources, links for analysis of proteins and nucleic acids, etc.
_________________________________________________________________________________________________