News

BMERC announces first Machine Learning Club of Spring semester

By Kathryn PorterMarch 6th, 2020in News
Please join us for the first meeting of the graduate student Machine Learning Journal Club this semester. We will discuss the paper "Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization", published in PLOS Comp.Bio. with the help of Jeffrey McMahan. 

Due to the recent developments related to the coronavirus (COVID-19) the first graduate student Machine Learning journal club of the semester will be POSTPONED to a later date (TBD).

Profs. Vajda and Paschalidis featured in Boston University ENGineer magazine

By Kathryn PorterJanuary 14th, 2020in News

The Fall 2019 issue of the BU College of Engineering Magazine highlights the importance of cross-disciplinary collaborations in facilitating scientific discoveries. The title article discusses the inspiration behind the Materials Science and Engineering (MSE) and Systems Engineering (SE) Divisions of the College of Engineering, which were created as a means of promoting research between Biomedical (BME), Mechanical (ME) and Electrical & Computer Engineering (ECE) departments. Several collaborative research projects are discussed, including the work of Professor Sandor Vajda (BME, SE) and Professor Ioannis Paschalidis (ECE, BME, SE) who have collaborated for decades on the development of automated servers for protein binding prediction.

Read the full article here: https://www.bu.edu/eng/2019/10/15/multiplication-by-divisions/

Highlights from the first Machine Learning Journal Club

By Zhuyezi SunSeptember 23rd, 2019in News

Our first BMERC-sponsored Machine Learning Journal Club was a blast! 20+ students and researchers from across different disciplines and departments such as Biomedical Engineering and Chemistry attended the event. This journal club was led by Israel and Megan from Prof. Sandor Vajda's group. We learned about basic concepts of supervised learning, followed by a hands-on session using scikit-learn and Jupyter Notebook.

Over 20 students and researchers attended the first journal club on Sep, 18th.
Israel led the discussion of supervised learning. Pictured is him explaining the concept of generalization loss.
The BMERC Machine Learning Journal Club is a monthly event. The aim of our journal club is to introduce fundamental concepts of machine learning to scientists and engineers, and to encourage discussions and conversations about the application of machine learning in our research (over pizza of course!). If you have any feedback or suggestions regarding this event, or if you would like to volunteer to lead a future session, please do not hesitate to contact us.

Stay tuned for the next event on Oct 23! We will be learning about unsupervised learning. 

BMERC RISE students conclude their summer research

By Kathryn PorterSeptember 1st, 2019in News

Boston University hosts high school students who are passionate about scientific research in the summer term. This is known as the Research in Science & Engineering (RISE) program. RISE students spend six weeks at the university and gain hands-on experience in the exciting cutting edge scientific research happening on campus. Research projects span a wide range of topics, including astronomy, biology, biomedical engineering, chemistry, electrical and computer engineering, mechanical engineering, medical laboratory research, neuroscience, physics, psychology, and public health.

This past summer BMERC affiliated labs accepted two RISE students, Raymond and Vijay. Raymond was mentored by graduate student Amanda Wakefield from the Vajda group. He conducted computational studies on protein binding sites. Vijay worked closely with Ashley Rebelo from Prof. Karen Allen's lab and worked on protein crystallization. At the end of the RISE program, both students presented their research at a poster symposium in front of an audience comprised of those familiar with research as well as the general public. Raymond's and Vijay's posters are titled "A Comparison of Computational and Experimental Methods for Determining Binding Sites of Proteins" and "Optimizing Crystallization Conditions of the N-terminal Domain of hAMPDA2 and Implementing a Baculovirus Expression System for hAMPD1 and 3" (see photos).

Raymond with Prof. Sandor Vajda and Prof. Karen Allen at the RISE Poster Symposium
Vijay presents his poster on protein crystallization research
Raymond at his poster discussing protein binding sites
Congratulations to Raymond and Vijay for a successful summer! It was our pleasure being RISE mentors and hosts.

 

For future interest in the BU RISE program, please find more information here.

The ClusPro protein-protein server is the best performer in the CAPRI46-CASP13 prediction competition

By Amanda WakefieldJuly 29th, 2019in News

ClusPro is a web server that performs rigid body docking of two proteins by sampling billions of conformations. The server has over 13,000 registered users and performs about 5,000 docking calculations each month. The two papers describing ClusPro have been cited over 1,500 times, and over 600 of these papers reported protein complex models built by the server. ClusPro has been participating in the CAPRI (Critical Assessment of Predicted Interactions), the ongoing communitywide experiment devoted to protein docking. In the CAPRI challenge, participating research groups and automated servers are given prediction targets, each being an unpublished experimentally determined structure of a protein-protein complex, and each group is expected predictions. The submitted models are evaluated by independent assessors. More recently CAPRI has been joined forces with the ongoing CASP (Critical Assessment of protein Structure Prediction), and most targets had to be predicted started from sequences rather than structures of component proteins.A homodimer prediction (cyan and blue) submitted by the ClusPro team which received a Medium quality score, overlapped with its crystal structure (wheat).

The most recent combined competition, CAPRI46-CASP13 was held during the summer of 2018 and has been evaluated on December 1-4 at the Iberostar Paraiso Maya resort on the Riviera Maya. The Vajda group was represented by graduate students Katie Porter and Israel Desta, who participated in the competition, in collaboration with the group of Prof. Dima Kozakov, a long-term member of BMERC, now an associate professor in the Department of Applied Mathematics at Stony Brook University. According to the evaluation at the meeting, ClusPro was the best performer in the server category. The server performance is described in the paper KA Porter et al., Template-Based Modeling by ClusPro in CASP13 and the Potential for Using Co-evolutionary Information in Docking, to be published in the journal Proteins: Structure, Function, and Bioinformatics.

Collaborative paper with visiting scientist from Brazil is published

By Amanda WakefieldJuly 20th, 2019in News

Dr. Marcelo Castilho, a Professor at the Universidade Federal da Bahia, spent two months working with the Vajda lab during the summer of 2018. The first paper resulting from this collaboration, TQ Froes et al. Structure-based druggability assessment of anti-virulence targets from Pseudomonas Aeruginosa, was published on April 17, 2019, in the journal Current Protein & Peptide Science. Dr. Castilho is a very driven scientist, and we were happy to have him in the lab. He was also working on a second paper while in the Vajda lab, and the paper is close to getting finished.

BMERC accepts RISE students

By Amanda WakefieldJuly 1st, 2019in News

The BMERC has accepted multiple high school students through the BU RISE program. These students work 40 hours a week for six weeks in one or more of our affiliated labs. This experience provides each of the students unparalleled access to both experimental and computational facilities.

Joint Grant Application Submitted for New Mass Spectrometer!

By Amanda WakefieldMay 31st, 2018in News

Abstract:

One of the main area of our research, supported by the MIRA grant R35 GM118078, entitled Analysis and Prediction of Molecular Interactions, is investigating the interactions between proteins and small molecules, including drugs and metabolites. Bioactive small molecules, such as the products of cellular metabolism, natural products and synthetic organic compounds, are potent mediators of biological processes as ligands and allosteric regulators. Mapping their physical associations is therefore a critical but challenging task. To this end, we seek NIGMS administrative supplements to acquire a high performance Thermo Scientific Q-Exactive Plus Orbitrap Mass Spectrometer (QE+MS) to support our efforts to explore and exploit the dynamic interactions of small molecules with cellular proteins, biochemical pathways and signaling cascades. We plan to use this instrument together with our new colleague and collaborator, Andrew Emili, a recent recruit to Boston University and leader in using mass spectrometry to map protein interaction networks, to study protein-metabolite interactions (PMIs) in a rigorous experimental manner. Our computational modeling predicts many novel interactions that require stringent experimental validation, which currently stretches the limited MS capabilities available to us. In addition to providing valuable information on potential PMIs, mass spectrometry will address a major challenge in differentiating putative functional regulatory interactions from non-specific interactions that do not entail functionality. This problem is an excellent fit for the structural modeling methods developed in our lab, and we will thus work in a synergistic, iterative manner to apply computational tools to analyze and prioritize experimental interaction data provided by the proposed mass spectrometry instrumentation for the identification of PMIs that are most likely functional. Although establishing functionality will still require other biological tests (e.g. enzyme assays), we expect to develop systematic methods that reduce the number of compounds that need to be investigated in such a demanding, low throughput manner. Having access to a state-of-the-art protein-metabolite interaction platform and our collaborations with Dr. Emili will be very productive and lead to fruitful new avenues for our research program. The collaboration will also engage us with the team of Dr. Daniel Segre at Boston University, whose lab studies complex metabolic networks, and thus will directly contribute to the identification of novel protein-metabolite interactions. Dr. Segre’s research is supported by the grant R01GM121950 “A platform for mining, visualization and design of microbial interaction networks”, and he is also requesting an administrative supplement to support the acquisition of the proposed mass spectrometer. The University’s commitment is demonstrated by its investment in renovating the infrastructure for supporting this multi-user research instrument and by the Department of Biology’s provision of partial support for an ongoing service contract to ensure its operation.

BMERC Open House draws in undergraduate crowd

By Amanda WakefieldMarch 19th, 2018in News

The recently held BMERC open house featured posters from labs across the Chemistry and Biomedical Engineering departments. The event successfully allowed graduate students and faculty members to engage undergraduate students in conversations about the many research projects going on at BMERC. Many undergraduate students were surprised at the wide variety of labs and their projects at Boston University and expressed interest in pursuing graduate degrees. Check back for updates on upcoming poster sessions!

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Zhuyezi Sun, a graduate student in the Vajda Lab, presents a poster on the ClusPro Server which was developed by the Vajda Lab.

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Margarita Tararina, a graduate student in the Allen Lab, presents her work on determining the structure of a protein within the HAD-Superfamily.

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Professor Vajda studies a poster on macrocycles authored by Lauren Viarengo (not pictured), a graduate student in the Whitty Lab. Israel Desta (left), a graduate student in the Vajda Lab, presents a poster about using machine learning to improve protein docking.